JN0-253 Exam Dumps - Juniper JNCIA-MistAI Questions and Answers

TheJuniper Mist AI platformis acloud-native, AI-driven network management solutionthat leverages machine learning and data science to provide predictive insights, proactive troubleshooting, and automated optimization acrosswireless, wired, and WANenvironments.

At the core of this intelligence is thePredictive Analytics and Correlation Engine (PACE), which powers Mist AI’s ability to process and analyze massive volumes of telemetry data in near real time.

According to theJuniper Mist AI Cloud Architecture Guide,

“The Predictive Analytics and Correlation Engine (PACE) collects, correlates, and analyzes pre-connection and post-connection user experience data, enabling real-time visibility and proactive detection of network anomalies.”

This allows Mist AI to perform the following:

Understand client onboarding and connectivity performance through SLE (Service Level Expectation) metrics.

Detect anomalies automatically and identify root causes with Marvis.

Continuously learn and improve via theMist AI efficacy loop.

OptionsA,C, andDare incorrect because:

Mist AI is fully automated and does not rely on manual data collection.

The Mist Cloud is the central data aggregation and analysis engine.

Marvisis proactive and autonomous, not dependent on user-driven troubleshooting.

Therefore, the correct answer isB. Juniper Mist AI uses Predictive Analytics and Correlation Engine (PACE) to collect and analyze pre-connection and post-connection user and location states in near real-time.

TheJuniper Mist Asset Visibilityservice provides real-time tracking and visibility for important devices and objects within indoor environments such as hospitals, offices, or warehouses. It usesBluetooth Low Energy (BLE)technology andMist vBLE-enabled access pointsto determine the precise location of tagged assets.

According to theJuniper Mist Location Services Guide, the feature is defined as:

“Asset Visibility leverages virtual Bluetooth LE technology and BLE tags to locate and track assets on floor plans in real time, providing actionable location-based intelligence.”

Key functionalities include:

Tracking BLE-tagged assets such as medical equipment, IT devices, or inventory.

Displaying live location information on floor maps.

Integrating with external asset management or workflow systems.

WhileUser Engagementfocuses on customer-facing location experiences (e.g., navigation or proximity marketing),Asset Visibilityis designed specifically for internal asset monitoring and operational efficiency.

Therefore, the correct answer isC. Asset Visibility.

Audit Logs in Juniper Mist are used to view a complete record of logins. The documentation states: "On the Audit Logs page, you can see who logged in to the Juniper Mist portal, when they logged in, and what they did." Audit Logs also record configuration and administrative actions by users on all sites within the organization, enabling administrators to track activity for compliance, troubleshooting, and security. This comprehensive record assists with accountability and change tracking, but they do not manage subscriptions, organization setup, or error logs for all devices. Filtering options allow for activity analysis over selectable time periods, by users, and by site to provide detailed insights into administrative behavior and user access history.​

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).

Marvis Minisis a feature withinMarvis Virtual Network Assistant (VNA)that proactively tests and validates network performance by simulating user connections. Instead of waiting for user complaints, it performssynthetic client transactionsto confirm the functionality of critical network services.

According to theJuniper Mist Marvis Minis Technical OverviewandMarvis AI Operations Guide, Minis validates several network functions automatically, including:

Dynamic Host Configuration Protocol (DHCP):Ensures clients can obtain IP addresses properly from DHCP servers, validating end-to-end DHCP exchange success and response time.

Address Resolution Protocol (ARP):Verifies correct IP-to-MAC address resolution, confirming that clients can reach devices on the same subnet and that ARP tables are updated correctly.

Marvis Minis also performs checks onDNS resolution, authentication, and application reachability, but not on SNMP or NTP. Those protocols are used for management and time synchronization, not end-user connectivity validation.

Thus, the correct answers areB (DHCP)andD (ARP).

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.

ThePredictive Analytics and Correlation Engine (PACE)is thecore AI and data analytics componentof the Juniper Mist Cloud architecture. It collects, processes, and correlates telemetry data across all managed domains —Wireless, Wired, and WAN Assurance— to deliver proactive insights and predictive network intelligence.

According to theJuniper Mist AI Operations and Architecture Guide:

“The Predictive Analytics and Correlation Engine (PACE) serves as the foundation of Mist AI, using continuous telemetry ingestion and machine learning algorithms to understand, correlate, and predict network behaviors across the wireless, wired, and WAN environments.”

PACE enables Mist AI to:

Detect anomalies in user experience and device performance.

Predict failures before they affect users.

Correlate events across network domains for root-cause analysis.

Therefore, the correct answer isA. Predictive Analytics and Correlation Engine (PACE).

In theJuniper Mist Marvis Actions dashboard, issues and recommendations are displayed with status labels indicating their progress and resolution method. One of these statuses isAI VALIDATED, which signifies that the issue was automatically detected, diagnosed, and resolved byMarvis AIwithout requiring manual intervention.

According to theJuniper Mist Marvis Virtual Network Assistant Operations Guide:

“AI VALIDATED indicates that Marvis has confirmed and resolved a network issue autonomously using AI-driven automation and telemetry correlation.”

This means Marvis performed the full troubleshooting cycle—identifying the anomaly, validating its cause, and confirming resolution—based on continuous monitoring and real-time network analytics.

Other statuses include:

UNRESOLVED:Issue is ongoing and needs attention.

RESOLVED:Marked manually by an administrator after resolution.

AI VALIDATED:Confirmed and closed automatically by Marvis AI.

Therefore, the correct answer isA. The issue was identified and resolved entirely by Marvis.

Juniper MistAccess Assuranceis a cloud-based network access control service that provides secure wired and wireless access through identity- and policy-based mechanisms. According to the official Juniper Mist AI documentation, Access Assurance usesuser and device identityto determine network access privileges dynamically.

The service enforces access policies primarily in two ways:

Assigning Specific Roles to Users:Access Assurance dynamically assigns roles to users and devices after successful authentication. These roles are used to apply specific network policies and permissions, defining what level of access or network resources a user or device is allowed. Roles can be leveraged in wireless SSID configurations or switch access policies to ensure consistent enforcement across the infrastructure.

Grouping Users into Network Segments:Access Assurance also allows grouping of users and devices intonetwork segmentsusing VLANs or Group-Based Policy (GBP) technology. This segmentation isolates users or devices into logical groups, ensuring security and optimized traffic handling. Policies are then applied to these groups to control communication between segments, thereby maintaining a zero-trust framework.

Options A and B are incorrect because Access Assurance does not establish VPN tunnels or passively monitor traffic as its primary method of access control. It relies instead onidentity-based role assignment and segmentationto enforce network security.

Marvis Minisis a component of theMarvis Virtual Network Assistant (VNA)within theJuniper Mist AI ecosystem. It is designed to proactively ensure optimal network performance and user experience by runningsynthetic network testsusing Mist-managed access points.

According to theJuniper Mist Marvis Minis Technical Overview, this feature allows APs to act asvirtual clientsthat automatically simulate user connection flows, including authentication, DHCP, DNS, and application reachability. These tests validate that thenetwork configuration and servicesare functioning as expected, even before real users experience issues.

The documentation states:

“Marvis Minis operates in conjunction with Mist AI to continuously validate network configurations and optimize user experience by identifying potential problems proactively.”

“Using Mist APs, Marvis Minis performs synthetic transactions to verify the performance of wireless, wired, and WAN segments without requiring external devices.”

Hence,Marvis Minis is not a support team (A),not a design AI model (B), andMarvis Actions (C)is a different feature for identifying and resolving live issues. The accurate description is thatMarvis Minis collaborates with Mist AI to validate configurations and optimize user experiences.