JN0-253 Mist AI - Associate (JNCIA-MistAI) Questions and Answers

In the Juniper Mist dashboard,Service Level Expectations (SLEs)are metrics that measure user experience in key areas such as connection, throughput, and roaming. Each SLE is composed ofclassifiers, which help identify the underlying cause of degraded performance or sub-threshold scores.

According to the Juniper Mist AI documentation, theRoaming SLEtracks client transitions between access points and evaluates the quality of those roaming events. The contributing classifiers typically includeSignal Quality,Wi-Fi Interference,Ethernet, andCapacity.

In this exhibit, the bar forCapacityis the longest under the “Roaming Classifiers” section, indicating that it has the most significant impact on theSub-ThresholdSLE value (10.6%). This means roaming performance is primarily being limited by insufficient capacity — often due to AP radio congestion or a high number of concurrent clients impacting handoff efficiency.

Hence, theCapacityclassifier is responsible for the sub-threshold SLEs.

Marvis, the AI-driven Virtual Network Assistant inJuniper Mist, uses continuous telemetry analysis and AI correlation to identifybad cable conditions. It does this by examining interface-level statistics gathered from switches and access points throughWired Assurance.

According to theJuniper Mist Marvis Operations and Troubleshooting Guide:

“Marvis detects bad cable issues by analyzing telemetry patterns such as CRC errors, FCS errors, packet drops, and link flaps that collectively match a known cable fault signature.”

When such patterns are detected, Marvis automatically generates anAI Actionindicating aBad Cableissue and identifies whether the problem is with theportor thecable. This proactive detection allows administrators to replace faulty hardware before it impacts network users.

Options A, B, and C are incorrect because Marvis does not perform active pinging, random packet captures, or random cable testing. Its detection is entirelyAI and telemetry-based.

Therefore, the correct answer isD. Marvis analyzes metrics, such as interface errors, that match a bad cable pattern.

In theJuniper Mist SD-WANsolution,device-specific WAN Edge templatesare used to streamline the deployment and configuration ofJuniper SRX or SSR (Session Smart Router)devices serving as WAN Edge nodes. These templates ensure consistent and accurate configurations across a distributed WAN environment while accounting for differences in hardware models and interface types.

According to theJuniper Mist WAN Assurance and SD-WAN Configuration Guide, device-specific templates:

“Automatically generate configuration elements tailored to the hardware platform, including interfaces, ports, and device capabilities.”

They are part of Mist’scloud-managed SD-WAN automation framework, which combines WAN Assurance and AI-driven insights to manage branch connectivity. The templates simplify provisioning by populating device-level parameters such as:

Interface naming and mapping based on the device model.

Hardware-specific configurations like tunnel endpoints, IP addressing, and routing settings.

Security and performance policies consistent with the organization’s SD-WAN design.

OptionsA,C, andDare incorrect because:

A(WLAN template automation) pertains to wireless network configuration, not WAN edge devices.

C(traffic inspection) relates to firewall or security policies handled by SRX’s UTM features, not templates.

D(monitoring and attack prevention) falls under Mist’s security or analytics capabilities, not the template function.

Therefore, the correct answer isB. To automatically generate configuration elements specific to device models.

Juniper Mist Wireless Assurance revolutionizes network troubleshooting by implementing Predictive Analytics and Correlation Engine (PACE) and dynamic packet capture. According to the official Mist documentation, PACE applies advanced data science and machine learning to analyze real network events and classify them for root-cause identification. The Mist PACE engine proactively identifies issues by correlating over 150 client and AP state changes, enabling the system to surface recommendations and automate root-cause resolution. This allows IT teams to move beyond reactive troubleshooting towards predictive and automated network operations, reducing time-to-resolution and minimizing user impact.

Additionally, dynamic packet capture significantly streamlines troubleshooting efforts. Mist Wireless Assurance automatically detects anomalies or failures in user and network behavior and instantly initiates a packet capture. These packet captures are contextually tagged to the affected event, stored in the cloud, and are readily accessible for analysis. This process eliminates the need for on-site technicians with sniffers, as now every major incident already has an associated packet capture, captured at the right moment. This capability greatly reduces troubleshooting time and ensures that issues can be reproduced and isolated accurately.

TheJuniper Mist Wired Assuranceplatform uses ahierarchical configuration modelto manage switch settings efficiently across organizations and sites. This hierarchy provides flexibility by allowing administrators to applyglobal configurationsthrough templates at theorganization level, while also permitting site-specific customizations.

According to theJuniper Mist Wired Assurance Configuration and Template Management Guide, the configuration hierarchy functions as follows:

“Switch templates can be created at both the organization and site levels. Organization-level templates define global configurations, while site-level templates provide location-specific customization that overrides the organization-level settings where applicable.”

This structure enables consistent policy deployment while preserving site autonomy for unique configurations. For example, global VLAN or QoS configurations can be managed at the organization level, and local templates can adjust settings for switch ports or device groups at specific sites.

Switch-specific overrides are allowed within the hierarchy, ensuring flexibility in cases where unique port or feature configurations are required.

Therefore:

Bis correct because switch templates exist at theorganization levelfor global use.

Cis correct because switch templates also exist at thesite levelfor localized adjustments.

Among Juniper Mist’sLocation-Based Services,Asset Visibilityprovides the most accurate location tracking capabilities. This is achieved through the use ofvBLE (virtual Bluetooth Low Energy)technology, which leverages a patented16-element BLE antenna arrayintegrated into Mist Access Points forAngle of Arrival (AoA)calculations.

According to theJuniper Mist Location-Based Services Technical Overview:

“Asset Visibility delivers sub-meter location accuracy by using BLE-based triangulation combined with Mist AI’s machine learning algorithms for continuous calibration.”

WhileWi-Fi locationoffers approximate device tracking based on signal strength and triangulation, andProximity Detectionidentifies nearby devices,Asset Visibilityprovides precise real-time tracking of BLE-tagged objects and devices.

User Engagement, on the other hand, focuses on customer-facing mobile interactions, not accuracy optimization.

Therefore, the correct answer isC. Asset Visibility.

TheMarvis Virtual Network Assistant (VNA)in Juniper Mist AI uses real-time telemetry and AI-driven correlation to identify hardware and connectivity issues, including bad cable conditions. When a“Bad Cable”alert is raised, Marvis analyzes physical link metrics from the switch and AP—such as CRC errors, FCS drops, and link flaps—to isolate the root cause.

According to the Juniper Mist AI Operations Guide, theMarvis Actions dashboardprovides contextual insights into the issue, showing whether the fault lies in thephysical cableitself or theswitch portit is connected to. Specifically, the dashboard highlights:

The affected device and port.

Whether the degradation originates from theport hardwareor thecabling.

Suggested corrective action (e.g., replace the cable or check switch hardware).

Marvis uses its AI-driven root cause analysis engine to distinguish between cable integrity problems and port failures by examining electrical signature anomalies and historical telemetry.

Options B, C, and D are incorrect because Marvis does not display cable category ratings or identify individual broken Ethernet pairs—it focuses on identifying and isolating the fault domain.

Therefore, the correct answer isA. If the port or cable is at fault.

The Juniper Mist REST API uses the JSON (JavaScript Object Notation) format for data exchange. The official Juniper Mist REST API overview states: “Juniper Mist uses REST APIs, which use HTTP methods (GET, POST, PUT, and DELETE) to transfer data in JavaScript Object Notation (JSON) format.” All interactions with the API involve sending request payloads in JSON, and receiving responses encoded in JSON as well. Juniper Mist’s automation and integration guides reinforce that the content type for API communications is always "application/json". Sample requests provided in the documentation, such as creation or feedback from POST, PUT, and GET methods, are displayed in JSON structure.

Unlike other formats such as YAML, XML, or protocol buffers, JSON is universally supported and highly favored for RESTful APIs because it is lightweight, human readable, and easily parsed by web and programming frameworks. This ensures consistency and compatibility across diverse integrations and automation workflows using the Mist platform.

Juniper Mist WAN Assuranceis a cloud-based service that extends Mist AI capabilities to the WAN edge, providing visibility, automation, and AI-driven analytics for WAN devices. It focuses on ensuringend-to-end service assurancefor users and applications across distributed networks.

According to theJuniper Mist WAN Assurance and SD-WAN Deployment Guide, the supported devices include:

“Juniper SRX Series Firewalls and Session Smart Routers (SSR) are integrated with Mist WAN Assurance for telemetry collection, service-level monitoring, and AI-driven troubleshooting.”

SRX Series Firewalls (A):Provide secure WAN connectivity and send real-time telemetry (including throughput, latency, and packet loss metrics) to Mist Cloud.

Session Smart Routers (C):Power the AI-driven SD-WAN solution with application-aware routing and session intelligence, fully integrated into Mist Cloud for advanced visibility and analytics.

EXandQFXswitches are used withWired Assurance, not WAN Assurance.

Therefore, the correct answers areA. SRX Series FirewallsandC. Session Smart Routers.

InJuniper Mist AI, variousmachine learning (ML)techniques are applied across the platform to analyze network telemetry and improve performance insights. Among these,unsupervised learningplays a critical role in identifying patterns, trends, and anomalies in unlabeled datasets—data that has not been pre-classified or annotated.

According to theJuniper Mist AI and Machine Learning Overview:

“Unsupervised learning enables Mist AI to automatically detect abnormal patterns or clusters in large volumes of unlabeled network data, allowing the system to identify anomalies and optimize network behavior without human labeling.”

This method allows Mist AI to autonomously recognize deviations in user experience, traffic behavior, or radio performance without prior definitions, helping to enhance predictive analytics and anomaly detection.

By contrast:

Supervised learningrequires labeled training data.

Reinforcement learninglearns through trial-and-error feedback loops.

Cognitive learningis not a formal ML category—it refers to human-inspired reasoning.

Therefore, the correct answer isD. Unsupervised learning.

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 theJuniper Mist WAN AssuranceandSD-WANframework,Forwarding Insightsis the feature responsible for providingapplication forwarding path visibility. It delivers detailed analytics on how application traffic is being routed across the WAN, enabling network administrators to understand and optimize application performance across multiple WAN links or paths.

According to theJuniper Mist WAN Assurance and Insights Documentation,Forwarding Insights:

“Provides visibility into the application forwarding path by showing which WAN link or tunnel is used for a specific flow, including health metrics such as latency, loss, and jitter.”

It integrates withMarvisand theAI-driven WAN Assurance engineto automatically correlate user experience with network transport behavior. Administrators can use Forwarding Insights to:

Identify whichpath (primary, secondary, or backup)an application flow takes.

Viewreal-time performance metricssuch as round-trip delay and packet loss per path.

Understandwhy path selection decisions were made, based on policy or link health.

Other options are incorrect:

A. Router Insightsfocuses on routing and device-level performance, not per-application path details.

B. WAN Edge Insightsprovides device health and site connectivity data, not application-level forwarding analytics.

D. Platform Insightscovers cloud infrastructure performance, not WAN traffic analysis.

Thus, the correct answer isC. Forwarding Insights.

Juniper Mist Cloud provides visual and automated notifications to alert administrators aboutsubscription status and expirationfor services such asWireless Assurance, Wired Assurance, WAN Assurance, Premium Analytics, and Marvis AI.

According to theJuniper Mist Cloud Administration and Licensing Guide, the system:

“Displays subscription and license expiration warnings in a banner across the top of the Mist portal interface when licenses are within their renewal window.”

This banner typically appears in yellow or red, depending on urgency, and includes direct links to theSubscriptionspage for renewal actions.

While subscription status information can also be viewed manually underOrganization → Subscriptions, thereal-time reminders and notificationsappear asbanner messages at the top of the Mist Portal.

OptionsB,C, andDare incorrect because:

Dashboard alerts focus on network events, not licensing.

Marvis Actions highlights operational or performance issues.

Device insights report performance metrics, not subscription data.

Therefore, the correct answer isA. In a banner message at the top of the Juniper Mist portal.

TheMist AI Efficacy Loopis a key concept within theJuniper Mist AI architecturethat ensures continuous improvement of itsmachine learning (ML)andartificial intelligence (AI)models. This process combines feedback and data collected from multiple sources — including real-world network telemetry, customer success feedback, domain experts, and the Mist data science team — to refine the AI algorithms and enhance prediction accuracy.

According to theJuniper Mist AI Operations and Architecture Guide, the process is described as follows:

“The Mist AI efficacy loop is a closed-loop feedback system that continuously collects data from the field, correlates it with expert knowledge and support insights, and uses it to retrain and improve AI models for greater accuracy and reliability.”

This iterative learning cycle allows Mist AI to:

Improve anomaly detection precision.

Reduce false positives in network issue detection.

Enhance Marvis’s ability to accurately identify root causes and recommend corrective actions.

Theefficacy loopis what differentiates Mist AI from static analytics platforms, as it creates aself-learning systemthat evolves with every deployment and customer interaction.

Therefore, the correct answer isB. Mist AI efficacy loop.

ThePredictive Analytics and Correlation Engine (PACE)is the core AI engine that powers theJuniper Mist Cloud. It is designed to continuously learn from real-time telemetry and user interactions across wireless, wired, and WAN networks to proactively identify anomalies and predict performance issues.

According to theJuniper Mist AI Cloud and PACE Architecture Documentation, PACE:

“Leverages machine learning and advanced analytics to correlate data across millions of network sessions, automatically identifying patterns that affect user experience.”

The engine continuously evaluates key Service Level Expectations (SLEs), such asTime to Connect,Throughput, andRoaming, to establish performance baselines and detect deviations before users notice them.

PACE doesnot rely on manual analysisoruser feedback, and it integrates telemetry rather than external monitoring tools to maintain a closed-loop feedback system for self-correction and optimization.

Therefore, PACE usesmachine learning (A)to understand, predict, and improve end-user experience across Juniper Mist-managed networks.

A DHCP lease must be obtained by the switchbefore the ZTP process proceeds. Juniper documentation clarifies: "Ensure that a DHCP server is reachable. In addition to providing an IP address to the switch, your DHCP server must provide the following information: a default gateway, an NTP server, and a DNS server address..." The initial event in the ZTP workflow is the switch receiving a valid IP address via DHCP. Only after obtaining an address can the switch connect to the Mist cloud and proceed with zero-touch provisioning. Other requirements, such as user account, NETCONF, or NTP sync, occur later or are handled automatically via cloud policy after onboarding.

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).​

TheAI-driven Radio Resource Management (RRM)feature inJuniper Mist Wireless Assurancedynamically optimizesradio resource settingsacross all managed access points (APs) to ensure optimal wireless coverage, capacity, and performance.

According to theJuniper Mist Wireless Assurance and RRM Guide, RRM continuously analyzes live network telemetry, including metrics such assignal strength, interference, channel utilization, and client distribution, to make intelligent adjustments in real time.

It automatically optimizes parameters such as:

Channel selection (to minimize co-channel and adjacent-channel interference).

Transmit power levels (to balance coverage and minimize contention).

Channel width (to optimize throughput based on RF conditions).

The documentation specifies:

“AI-driven RRM in Mist Cloud continuously learns and adapts radio configurations based on environmental and client behavior patterns, improving network stability and overall user experience.”

OptionsA,C, andDare incorrect because:

Band steeringis a specific feature handled separately within WLAN settings.

SSID naming conventionsanduser interfacesare administrative, not RRM-controlled.

Therefore, the correct answer isB. Radio resource settings.

Juniper Mist’svirtual Bluetooth Low Energy (vBLE)technology is designed to deliverprecise indoor location servicesusing cloud-managed access points equipped with integrated BLE antenna arrays. The system supports multiple operational modes, includingEngagement Mode(for mobile app interactions) andAsset Visibility Mode(for BLE tag tracking).

According to theJuniper Mist Location Services Documentation, inAsset Visibility Mode, the vBLE antenna functions primarily inreceive modeto detect and process signals emitted fromBLE asset tags. These tags periodically transmit Bluetooth “chirps” that are received by multiple APs. Mist Cloud then usesangle-of-arrival (AoA)andRSSI triangulation algorithmsto determine the exact location of the asset within the facility.

The documentation specifies:

“In Asset Visibility Mode, the vBLE antenna operates in receive mode and listens for BLE tag beacons (chirps). The system triangulates these signals to calculate the real-time location of tracked assets.”

Conversely,Engagement Modeis the configuration in which vBLE operates intransmit modeto interact with mobile devices running the Mist SDK — which corresponds to location-based engagement or proximity notifications.

Thus, the correct answers are:

A. The vBLE antenna is in the receive mode

B. The vBLE antenna tracks chirps from BLE tags

Marvis Minisis an advanced feature within the Juniper Mist AI ecosystem designed to performautonomous, synthetic network testing. It uses Mist Access Points (APs) to simulate client behavior—such as association, authentication, DHCP, DNS, and application reachability—to proactively detect service issuesbefore real users are affected.

According to theJuniper Mist Marvis Minis Deployment GuideandMarvis AI documentation, the key requirement for enabling Marvis Minis is that all participating access points must be running aminimum supported firmware versionthat includes the Minis agent functionality.

The documentation specifies:

“Marvis Minis requires APs running the minimum firmware version that supports synthetic testing. APs on earlier versions will not be capable of running Minis tests or reporting results to the Mist Cloud.”

Additional subscriptions such asWAN Assurance,Premium Analytics, orWLAN templatesare not prerequisites for operation. WhileMarvis licensingmust be active, the feature itself relies primarily on compatible firmware within the Mist-managed APs.

Therefore, the correct answer isC. Minimum AP firmware— ensuring the APs are on a supported firmware release is essential for Marvis Minis functionality.

InJuniper Mist AI,Service Level Expectations (SLEs)form the foundation ofWireless AssuranceandWired Assurance. They provide adata-driven, proactive methodto measure and maintain the quality of user experience, going beyond traditional device-centric monitoring.

According to theJuniper Mist AI Operations GuideandWireless Assurance Documentation, SLEs:

“Leverage machine learning and data science to deliver a proactive understanding of end-user experience and identify root causes of performance issues.”

Each SLE (such asTime to Connect,Roaming,Throughput,Coverage, andCapacity) is composed ofclassifiers, which break down performance metrics into measurable, root-cause categories. Examples includeDHCP,DNS,Authentication, andSignal Qualityclassifiers.

This classifier-based structure enables Mist AI to automatically correlate problems and highlight the most probable cause of degradation—eliminating the need for manual troubleshooting or reactive analysis.

OptionsBandDare incorrect because SLEs arenot ad hoc toolsfor manual troubleshooting and donot simply list connected clients. Instead, they provide intelligent, AI-driven insights into user experience across the network.

Therefore, the correct statements are:

A. SLEs use machine learning to provide a proactive approach to understanding the end-user experience.

C. The metrics analyzed to meet specific SLE goals are categorized into classifiers.

When developing areal-time visualization dashboardthat displays client locations on a map, Juniper Mist offers specific APIs and data streaming methods to support dynamic updates.

According to the Juniper Mist Developer Documentation, theWebSocketinterface enables continuous,real-time streaming of client location and telemetry datadirectly from the Mist Cloud. This mechanism is ideal for live dashboards, as it eliminates the need for repeated REST API polling. WebSocket connections provide instant updates whenever a device moves, connects, or disconnects, ensuring the displayed map remains accurate in real time.

TheLive Viewfeature complements this functionality within the Mist Cloud and third-party integrations. It allows administrators and developers toview live location movements of Wi-Fi clients, BLE beacons, and IoT deviceswithin a site’s floor plan. It uses telemetry directly from access points, offering second-by-second updates.

In contrast,RESTful APIsandWebhooksare designed for event-based automation and configuration management rather than live visualization. REST APIs are best for historical or static data retrieval, while Webhooks are used for triggering external actions based on events.

Therefore, the correct functions for real-time map visualization are:

WebSocket (C)— for continuous live data streaming

Live View (D)— for direct map-based visualization of client activity

From Juniper’s official guide:

“You’ll need either a claim code or an activation code to claim an AP. With either, you can claim an AP by using one of the following methods:

Mist AI Mobile App

A Web browser

You can claim either a single AP using a claim code or multiple APs using an activation code. You can use any of these methods to claim an AP:

To claim a single AP, use the claim/QR code located on the rear of the AP.

To claim multiple APs, you’ll need to use an activation code. When you purchase multiple APs, we provide you with an activation code along with your PO information.”​

From the Mist documentation:

“APs can be claimed to any organization by using either the activation code, claim code or QR code.

Activation Code: Whenever you order APs, our Sales Operations team will send you an activation code which can be used for claiming the APs and subscriptions as per the order. …

AP Claim Code: You can individually claim APs to your organization by navigating to Organization > Inventory > Claim APs and entering in the claim code found on the back of each AP.

AP QR Code: Using our Mist AI mobile app you can scan the QR code printed on the back of our APs to claim APs to your organization.”​

Summary:

The Juniper Mist platform allows you to claim an Access Point using:

Activation code (provided for bulk purchases, via PO)

Claim code (unique per AP, on the rear label)

QR code (scanned with the Mist AI mobile app, also encoded as the claim code)

These extracts are direct from Juniper’s own documentation and confirm the methods for AP onboarding in the Mist platform.

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.

When creating a new site in the Juniper Mist User Interface, the three required configuration settings are Site Name, Country, and Location. According to Juniper Mist's official configuration guides: "At a minimum, enter the name, time zone, and location..." The 'Information' section of site setup requires the Site Name (a descriptive name to identify the site), Country (which sets regulatory and RF domain requirements), and Location (address or geo-coordinates for the site). These form the basis of the site identity in the Mist cloud and are mandatory for dashboard visibility, compliance, and baseline RF configuration. An RF Template, though critical for wireless tuning, is optional and can be assigned post-site creation. Active Hours are not required for the default site setup and are related to scheduling analytics or location-based services, not to the core creation workflow.

TheJuniper Mist Cloud portalprovides a user-friendly interface that supports multiple languages to enhance accessibility for global users. The language preference determines the display language for menus, dashboards, and configuration pages across the Mist UI.

According to theJuniper Mist Cloud Administration Guide, the portal’s language can be modified as follows:

“Users can change the display language of the Mist portal using the Change Language drop-down list located in the upper-right corner of the interface.”

This option allows users to immediately switch the UI language without affecting other users in the organization or requiring administrative permissions. The change is applied per user profile and is stored for future sessions.

Other listed options are invalid:

A:The Alerts page does not include language settings.

B:The My Account page shows personal info but not display language options.

C:Organization templates are unrelated to UI preferences.

Therefore, the correct answer isD. Use the Change Language drop-down list of the Juniper Mist portal.

When a customer requests asubscription renewalfor Juniper Mist services via e-mail, the process is handled through a coordinated workflow between theJuniper Mist Cloud licensing systemandJuniper Support. The renewal request ensures that existing service entitlements—such asWireless Assurance,Wired Assurance,WAN Assurance,Marvis AI, orPremium Analytics—continue without interruption.

According to theJuniper Mist Cloud Licensing and Subscription Management Guide, the renewal workflow is described as follows:

“When a renewal request is submitted via e-mail, Juniper Mist support receives and validates the request, initiates processing for the selected subscriptions, and issues a new activation code once the renewal is completed.”

Here’s what happens after the renewal request:

B.The Juniper Mist systemsends a confirmation e-mailacknowledging the renewal request and routes it tosupport for processing.

C.Once processed,Juniper Mist generates and delivers an activation codevia e-mail that must be entered into the Mist portal to activate the renewed subscription(s).

Incorrect options:

A:No promotional materials or physical packages are sent.

D:A cancellation notice is not sent for renewal requests; it applies only to expired or terminated subscriptions.

Therefore, the correct answers areB. Juniper Mist e-mails the support request for the selected subscriptionsandC. Juniper Mist processes the order and sends an activation code.