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Routing Assuranceis a feature of theJuniper Mist WAN Assurancesolution, providing AI-driven visibility, analytics, and troubleshooting forJuniper Session Smart Routers (SSR)deployed in SD-WAN environments. The system monitors routing performance, link health, and application traffic to ensure reliable WAN connectivity and performance.

According to theJuniper Mist WAN Assurance and Routing Assurance Guide, the feature is described as:

“Routing Assurance provides continuous monitoring of routing operations and path decisions for Juniper Session Smart Routers, offering AI-driven insights into application routing behavior and WAN path health.”

TheSession Smart Router (SSR)platform—powered by128 Technology(acquired by Juniper Networks)—is specifically designed for AI-driven, session-aware routing. It integrates seamlessly with Mist Cloud to:

Track routing changes and path selection decisions.

Correlate application experience with routing behavior.

Identify and remediate path-related issues automatically through Marvis AI.

Other devices serve different functions:

MX Series– Carrier-grade routing, not used in Mist Routing Assurance.

EX Series– Switches used for Wired Assurance.

SRX Series– Firewalls supporting WAN Assurance and security but not Routing Assurance.

Therefore, the correct answer isC. Session Smart Routers.

In theJuniper Mist Cloud, theClient Eventssection within theMonitoringinterface displays detailed event logs for both wired and wireless clients, providing insights into connectivity, authentication, and performance-related activities. Each event entry may include associated diagnostic files such asdynamic packet captures (DPCs),traceroute data, andsyslogsdepending on the event type and device context.

According to theJuniper Mist AI Operations and Client Event Diagnostics Guide, the platform states:

“Wireless client events provide correlation between client connection attempts and associated diagnostic artifacts such as dynamic packet captures. These files are generated automatically during troubleshooting events and are attached to the event log for administrator review.”

From the exhibit, theclient is shown as a wireless device, indicated by theWi-Fi iconand theSSID association informationvisible in the event details. Additionally, the entry confirms that adynamic packet capture (DPC)file was automatically generated for the event, allowing engineers to download and inspect packet-level activity for root-cause analysis.

Therefore:

B (It is a wireless client)is correct — the event pertains to a Wi-Fi-connected device.

C (A dynamic packet capture file is included)is correct — the log includes a downloadable DPC file.

InJuniper Mist’s Location-Based Services, theAsset Visibilityservice utilizes the built-inBluetooth Low Energy (BLE)antenna array within Mist Access Points to track BLE tags and devices inlisten-only mode. This allows the APs to receive BLE signals emitted by assets and compute their real-time location usingangle-of-arrival (AoA)andRSSI-based triangulation.

According to theJuniper Mist Asset Visibility and Location Services Guide:

“When operating in Asset Visibility mode, the vBLE antenna array in Mist Access Points functions in listen-only mode, collecting BLE chirps from asset tags and relaying this data to the Mist Cloud for location determination.”

This configuration differs fromvBLE Engagement, where APs transmit BLE beacons to interact with mobile apps. InAsset Visibility, the BLE array passively listens to track tagged assets (e.g., equipment, IoT devices) across a defined floor map.

Therefore, the correct answer isD. Asset Visibility.

In Juniper Mist AI,Wireless Assurance Service Level Expectations (SLEs)are designed to provideAI-driven visibility into user experience and network performance. Each SLE represents a specific aspect of the end-user journey — such asTime to Connect, Throughput, Coverage, Roaming, Capacity, and Application Experience.

According to the Juniper Mist documentation, SLEs “define measurable benchmarks for user experienceand identify where deviations occur.” This allows administrators to quickly determine whether issues stem from client devices, access points, wired uplinks, or WAN connectivity. When an SLE metric falls below its threshold, Mist AI automatically highlights the affected classifier (for example, DHCP, DNS, or Wi-Fi interference) and providesroot-cause correlationthrough AI-driven insights.

This data-driven approach enables administrators totroubleshoot proactivelyby focusing on user-impacting areas instead of raw device statistics. Thus, Wireless Assurance SLEs act asexperience-based benchmarksthat simplify troubleshooting, improve performance visibility, and shorten mean time to repair (MTTR).