Practice Free JN0-253 Mist AI - Associate (JNCIA-MistAI) Exam Questions Answers With Explanation

Thepacket capture featureinJuniper Mist Cloudallows administrators to remotely capture live network traffic from managed devices such as Access Points (APs) or switches for detailed troubleshooting.

According to theJuniper Mist Network Troubleshooting and Diagnostics Guide:

“Once a packet capture session is stopped or completed, the captured data is saved as a downloadable .pcap file that can be analyzed offline using tools such as Wireshark.”

This ensures administrators can inspect packet-level details for issues such as authentication failures, DHCP errors, or connectivity drops. The data is stored temporarily and made available through the Mist UI for download before automatic cleanup.

OptionsB,C, andDare incorrect because captured data is not stored permanently in the cloud, does not trigger automated alerts, and is not discarded immediately. The purpose is to make the data accessible foroffline inspection and analysis.

Therefore, the correct answer isA. It is saved as a downloadable capture file for offline inspection.

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).

TheJuniper Mist Cloud APIfollowsRESTful API design principles, enabling programmatic access to all Mist Cloud functions such as device management, configuration, analytics, and monitoring. REST APIs in Mist use a lightweight and standardized data exchange format to facilitate seamless integration with third-party applications and automation frameworks.

According to theJuniper Mist API Developer Guide:

“All Juniper Mist Cloud API requests and responses are transmitted in JavaScript Object Notation (JSON) format. JSON is used because it is lightweight, easy to parse, and compatible with all modern programming environments.”

JSON is the preferred format because it is both human-readable and machine-efficient, allowing for fast serialization and deserialization of data structures.

Other formats such asCSV,XML, andYAMLare not used for API communication within the Mist Cloud architecture.

Therefore, the correct answer isD. JSON.

Marvis Minis validates network configurations automatically and uses supervised machine learning. As stated in the Juniper Mist AI documentation, “Marvis Minis runs validations automatically at regular intervals and can be triggered manually by administrators. Minis use network digital twin technology and supervised machine learning to simulate and validate real-world user connectivity events.” The system automatically creates patterns, triggers tests, and correlates real user and simulated network behaviors with the learned models. The validation covers critical network services—such as DHCP, DNS, ARP, and application reachability—and does so across various scopes (site, AP, VLAN, and switch). There is no requirement for additional hardware, as the digital twin reuses existing network infrastructure and existing APs.

The appropriate solution is Juniper Mist Asset Visibility (option C). Asset Visibility is a cloud service that leverages Juniper Mist Access Points and virtual Bluetooth Low Energy (vBLE) technology to track, locate, and display all network devices—including both Juniper and non-Juniper hardware—within the Mist GUI. According to the official Juniper documentation: “Juniper Mist Asset Visibility unites Wi-Fi connectivity, indoor location services for asset tracking, and IoT visibility in a single cloud platform. By combining vBLE with the Mist Cloud, organizations can use the same infrastructure—even when wired switches are from different vendors—for locating, tracking, and analyzing their most valuable assets and network devices.”

This capability is independent of switch manufacturer and provides comprehensive visualization of wireless APs and connected wired devices, ensuring a true single-pane-of-glass management experience. Wired Assurance, Marvis Actions, and LLDP-enabled Wi-Fi Management may provide visibility and proactive troubleshooting, but only Asset Visibility guarantees display and tracking of all assets—Juniper and non-Juniper—in the Mist GUI.

To view an organization’s Audit Logs in the Juniper Mist UI, the required roles are Network Admin and Super User. According to Juniper Mist documentation: “Network Admin (with All Sites access) and Super User roles grant permission to view and interact with organization-level features, including Audit Logs and Inventory.” The Audit Logs page provides a chronological record of user logins and configuration changes, and access is restricted to authorized users for security and compliance reasons. The "Super User" role has full read/write access for the entire organization—no restrictions—allowing these users to view Audit Logs without limitation. The "Network Admin" role, when granted access to All Sites (not just specific sites), can also view Audit Logs as part of their permitted organization-level operations. Other roles, such as Helpdesk and Installer, have limited or specific access and cannot access Audit Logs. These permissions ensure that only trusted network administrators and super users have the necessary authority for sensitive audit and compliance functions.

A self-driving AI network is comprised of two foundational components: actions and telemetry. According to Juniper’s own communications, "Marvis AI analyzes telemetry across the wired, wireless, WAN and data center domains, and creates automated workflows to simplify operations and lower costs. Agentic AI: Accelerating self-driving operations." Telemetry provides real-time continuous data and metrics from the network, including client, device, and application health, enabling the AI engine to build a current, actionable state model. Actions refer to proactive, automated tasks performed by the AI, such as remediating misconfigured ports, resolving anomalies, optimizing performance, and self-healing operations—"Expanded Self-Driving Actions… the Marvis Actions dashboard now supports the autonomous remediation of more network issues." Human interface and support tickets are beneficial for management and support, but the core capabilities of a self-driving AI network are telemetry (data/observability) and actions (automation/remediation).?

A high percentage of Asymmetry Uplink errors indicates coverage holes caused by asymmetric uplink strength between the AP and client devices. According to Juniper Mist's official documentation: "Asymmetry Uplink—Clients received a weak signal due to asymmetric uplink strength between the AP and the client device. (Uplink traffic is the traffic going from the client to the AP, and then to the Internet.) Asymmetry can occur for various reasons, such as clients being too far from the AP." This generally means that clients are physically located at a distance or behind obstacles (such as walls), causing the AP to detect weak signals from those clients. Coverage holes arise when APs are placed such that some areas have insufficient RF coverage, and the low-powered client devices cannot maintain reliable communication with the AP—even though the AP, with its higher transmit power, might hear the client, the client cannot send strong enough signals back. The SLE classifier is designed to highlight such areas for remediation, prompting network admins to review and enhance AP placement or signal thresholds.

To enable Juniper Mist Access Assurance for 802.1X (RADIUS) authentication with Cisco APs, the correct approach is to configure a new 802.1X SSID on the Cisco AP referencing your Juniper Mist Edge as the RADIUS server (option C). According to Juniper Mist’s official documentation and architecture guides: “Mist Access Assurance supports end-client authentication on third-party infrastructure by leveraging the Mist Auth Proxy application running on a Mist Edge platform. Third-party devices, such as Cisco APs, are added as RADIUS clients at Mist Edge. The Mist Edge proxy handles all RADIUS authentication traffic from the APs, wraps these authentication requests into a secure RadSec tunnel, and relays them to the Mist Access Assurance cloud for validation against configured authentication rules.”

This deployment does not require direct RADSEC tunneling from Cisco APs to Mist Access Assurance (since Cisco APs are not natively RADSEC capable) but uses Mist Edge as an intermediary RADIUS server and authentication proxy. "Add an authentication rule in Access Assurance to permit user access," enabling centralized management and policy enforcement in the Mist Cloud.

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).

Juniper Mist Wired Assurance delivers robust automation for campus and remote switches by supporting both template-based configuration for switches and port profiles as core features. According to the official Juniper Mist documentation, "Wired Assurance provides cloud-managed switch configuration through scalable templates. These templates are set at the organization or site level, standardizing VLANs, port settings, security options, and other operational parameters for all managed EX and QFX series switches." Furthermore, port profiles allow administrators to automate port assignment and behavior based on dynamic criteria such as LLDP information or MAC addresses: "Dynamic port profiles are applied automatically when specific criteria are detected, simplifying operational workflows and reducing manual errors."

Features like "template-based configuration for routers" and "WxLAN policies" are not part of Mist Wired Assurance. Router configuration is enabled in Routing Assurance, and WxLAN is a Juniper-specific campus automation solution, not directly related to switch management.

Verification:

This aligns with the selections marked in your image ("template-based configuration for switches" and "port profiles"). It is fully verified by Juniper's official guides for Mist Wired Assurance.

The fundamental sampling method used in supervised learning is a labeled dataset. As described in Juniper Mist AI and machine learning application guides, supervised learning algorithms are trained using datasets in which each sample is paired with a known output (label). The model is fed examples comprising input data and the correct answer, learning patterns to map new inputs to their target outputs. While regression, decision tree, and random forest are techniques within supervised learning, the process fundamentally relies on having a labeled dataset for both training and validation phases. “Supervised machine learning models are built on labeled data, with each input paired to a target value or classification.” This allows for accurate model training and evaluation.

Juniper Mist Location Services provide asset location and wayfinding. According to official Juniper documentation: "Juniper Mist provides location accuracy for wayfinding, asset visibility, and user engagement," leveraging cloud-native vBLE and Wi-Fi technologies.

Asset location enables organizations to locate high-value resources, personnel, or IoT devices in real time with rich analytics, making it easy to find assets and people using the Mist dashboard and APIs.

Wayfinding gives users turn-by-turn indoor navigation and mapping via mobile SDKs and the Mist cloud.While geofencing can be achieved as part of location-based engagement features, it is not listed as a primary Mist Location Service solution. GPS location is not directly supported; Mist Location Services operate indoors using Wi-Fi and BLE signals, not satellite GPS.

In theJuniper Mist Cloud licensing model, subscriptions represent service entitlements that enable specific features such asWireless Assurance,Wired Assurance,WAN Assurance,Marvis Virtual Network Assistant, andPremium Analytics. These subscriptions are managed at theorganization leveland are not permanently tied to individual hardware units.

According to theJuniper Mist Licensing and Subscription Management Guide, subscriptions are:

“Cloud-based entitlements associated with an organization, not bound to specific device serial numbers. Devices draw from the subscription pool dynamically.”

This design allows flexibility and simplifies device replacement or scaling:

When a new device (for example, an access point or switch) is added to the organization, thesubscription is automatically assignedto it from the available pool.

If a device isremoved or fails, the subscription is automaticallyreleased and reassignedto a replacement unit—no manual transfer is required.

Therefore:

Ais correct because subscriptions are not linked to a single device’s serial number.

Dis correct because subscriptions automatically reapply when replacement devices are onboarded.

OptionsBandCare incorrect because Juniper Mist subscriptions are organization-based, not hardware-bound, and require no manual reassignment after device failure or replacement.

Bad cables are identified under the Layer 1 category within Marvis Actions. Juniper Mist’s documentation states: "Use the Actions dashboard to resolve Layer 1 issues. When you click the Layer 1 button on the Action dashboard, all available Layer 1 actions appear. This category currently contains only one action: bad cable." Marvis can detect and alert for bad cables based on frame errors, link statistics, and AP/Switch behavior, all under the Layer 1 category. Connectivity, security, and client issues are handled under their respective action categories, but bad cabling is specifically monitored and detected as a physical (Layer 1) fault.

In theJuniper Mist Cloud platform, each organization is automatically assigned a uniqueOrganization IDupon creation. This ID serves as apermanent, system-generated identifierused for API authentication, integration, and cross-service communication.

According to theJuniper Mist Cloud Administration and API Integration Guide:

“Organization IDs are automatically generated by the Mist Cloud at the time of organization creation and are read-only system values that cannot be edited or modified by administrators.”

This ensures that every organization is uniquely identifiable across Mist’s distributed cloud infrastructure. The Organization ID remains consistent even if the organization name or configuration changes.

Therefore, the correct answer isD. They are read-only.

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.

TheAI-driven Radio Resource Management (RRM)system inJuniper Mist Wireless Assuranceemploysreinforcement learningto continuously optimize wireless radio parameters such as channel selection, transmit power, and channel width.

According to theJuniper Mist Wireless Assurance and AI-Driven RRM Guide:

“The RRM system leverages reinforcement learning techniques to dynamically adjust radio configurations based on environmental conditions, user density, and interference patterns.”

Reinforcement learning enables the Mist AI system to make decisions by continuously evaluating the outcome of past configurations and improving future adjustments. This ensures that Mist RRM can autonomously optimize RF conditions for coverage and capacity without manual intervention.

Therefore, the correct answer isC. Reinforcement learning.

Marvis Miniscontinuously validates the health of network services by performing synthetic tests at predefined intervals without requiring user intervention. These tests simulate real client interactions — such as authentication, DHCP, DNS, and application reachability — to detect network issues proactively.

According to theJuniper Mist Marvis Minis Technical Overview, the feature performs:

“Automated validations every hour to ensure wireless, wired, and WAN network services are operating as expected.”

Each validation cycle allows the Minis agent (running on Mist Access Points) to verify connectivity and performance parameters across key stages of the client experience. If any issues are detected, they are automatically surfaced in theMarvis Actions dashboardfor further analysis.

While administrators can trigger additional manual tests,automatic validations occur every hourby default across all enabled sites.

Therefore, the correct answer isB. Every hour.

In theJuniper Mist Wireless Assurance dashboard, eachService Level Expectation (SLE)is broken down intosub-classifiersto identify the specific causes of degraded user experience. For theCapacity SLE, Mist AI analyzes performance indicators related to access point utilization, airtime availability, client density, and radio congestion.

According to theJuniper Mist Wireless Assurance Analytics Guide, sub-classifiers within the Capacity SLE may include:

WiFi Interference– measures co-channel and adjacent-channel interference.

Capacity– monitors total bandwidth and airtime utilization.

Network Issues– highlights backend transport or switching congestion.

Excessive Client Load– indicates when too many clients are associated with a single access point or radio, leading to reduced throughput and contention.

In the exhibit, theExcessive Client Loadbar clearly shows the highest contribution to the Capacity SLE degradation. This means that the majority of capacity issues were caused byan overloaded access point or radio channelhandling more clients than optimal.

Therefore, the correct answer isD. Excessive Client Load.

TheJuniper Mist Cloud platformis built on amicroservices-based architecture, where individual software components perform specific functions and communicate using well-definedApplication Programming Interfaces (APIs).

According to theJuniper Mist Cloud Architecture and Operations Guide:

“Microservices communicate through secure APIs, allowing independent services to interact seamlessly while maintaining modularity and isolation.”

This architectural design provides major operational benefits, including:

Independent scalability– each service can scale based on workload demand.

Fault isolation– failures in one service do not affect others.

Continuous deployment– updates can be made to one service without impacting the rest of the platform.

Incorrect options:

B:Juniper Mist microservices are independently updated, not deployed as one suite.

C:They are independent, not dependent on one another.

D:Each microservice maintains its own data model; they do not rely on a single shared database.

Thus, the correct answer isA. Microservices communicate with each other using APIs.

Alerts represent network and device issues that are ongoing. Juniper Mist™ categorizes them as follows:

Infrastructure Alerts—Repeated events involving servers and protocols that can potentially affect a large number of clients. For example, an event during which a Domain Name System (DNS), Dynamic Host Configuration Protocol (DHCP), or RADIUS server is unreachable can affect many clients. Similarly, if a power supply on a switch is in alarm state, a large number of clients and a large amount of traffic could be affected.

Marvis Alerts—Repeated events that Marvis tracks on the Marvis Actions dashboard. For example, if an access point (AP) regularly fails health checks, you'll see a Marvis alert for it.

Security Alerts—Repeated events that could dramatically affect network security. For example, these alerts appear if a rogue AP is detected and clients start connecting to it.

Certificate Alerts—Notification for expired, and soon-to-expire, user-added digital certificates. These include RadSec (configured at Organization > Settings > RadSec Certificates and AP RadSec certificate), SSO (configured at Organization > Settings > Single Sign-On), and PSK Portal IDP certificates (configured at Organization > Client Onboarding). Certificate alerts appear on the Alerts page and begin 30 days before the certificate's expiry date, then the notification repeats 15, 7, 3, and 1 day before expiration unless the certificate is renewed. .

https://www.juniper.net/documentation/us/en/software/mist/mist-aiops/topics/concept/alerts-overview.html

The WAN Edge Health SLE in Juniper Mist monitors critical operational metrics for WAN edge devices. According to Juniper’s documentation: “Juniper Mist analyzes various factors that affect WAN edge health and assigns a score… Classifiers include Memory—triggered when WAN edge memory utilization is above 80 percent and CPU—triggered when control or data plane CPU utilization is above 90 percent.” These components directly impact the device’s ability to process traffic. Monitoring these parameters enables rapid detection of system resource constraints, which are essential for ensuring optimal WAN performance. While ISP reachability is a separate SLE (usually part of WAN Link SLEs), application response times are tracked in Application SLEs.

The Juniper Mist REST API primarily provides functions for Juniper Mist configuration and historic statistics monitoring. According to the Juniper Mist documentation and API reference, the REST API allows users to automate configuration changes and retrieve historical data for analysis and reporting. Specifically, “configuration” functions include creating, updating, and deleting sites, devices, SSIDs, VLANs, templates, and user roles through API calls. “Historic statistics monitoring” refers to the API’s capability to pull time-series analytics on network and device performance, enabling users to query device usage, client events, SLE metrics, and application data over customizable timeframes.

Real-time statistics and event-driven monitoring are typically accessed via Mist’s WebSocket API, not the REST API. The REST API focuses on configuration management and historical data extraction for audit and trend analysis, supporting full automation and integration with third-party tools.

Verification:

These answers match the selections marked in your image ("Juniper Mist configuration" and "historic statistics monitoring") and are verified per Juniper’s API documentation and feature matrix.

Radio Resource Management (RRM)is a key feature ofJuniper Mist Wireless Assurancethat uses AI-driven automation to dynamically adjust radio settings across access points (APs) for optimal wireless performance. The RRM engine ensures proper channel assignment, transmit power control, and interference management across the network.

According to theJuniper Mist Wireless Assurance and AI-Driven RRM Guide, RRM operates intwo modes:

Event-Driven RRM:This mode reacts immediately to real-time changes in the RF environment, such as new access points, interference spikes, or client density changes.

Global Optimization RRM:This process runs as ascheduled, system-wide optimization once per dayto evaluate the overall RF environment and redistribute channels and power settings network-wide for the best balance of coverage and capacity.

The documentation states:

“The RRM global optimization algorithm automatically executes once daily to ensure optimal channel and power planning across all APs.”

Thus, the correct answer isD – The RRM global optimization system automatically runs once a day.