JN0-252 Mist AI- Associate (JNCIA-MistAI) Questions and Answers

Site Level: WLAN objects can be created at the site level, allowing specific configurations for different locations within an organization. This helps in customizing WLAN settings based on the unique requirements of each site.

Org Level: WLAN objects can also be created at the organization level, which provides a standardized configuration that can be applied across multiple sites. This ensures consistency in WLAN settings throughout the entire organization.

References:

Juniper Mist WLAN Configuration Guide

Site and Org Level Configration.

Identify the Scenario: Five clients on the network and 20 minutes of statistics for each client.

Calculation:

User Minutes = Number of Clients × Duration of Statistics.

User Minutes = 5 clients × 20 minutes per client.

User Minutes = 100.

Conclusion:

The total user minutes in this scenario is 100.

References:

Mist Documentation on User Minutes: Mist Documentation

The "Exceeded" status for a subscription means that the allowed usage defined within the subscription has been surpassed.

This typically refers to exceeding limits such as the number of devices, data usage, or other metrics specified in the subscription plan.

Exceeding these limits may require action such as upgrading the subscription plan to accommodate the additional usage.

Reference: Juniper Networks documentation on subscription status and management.

Supported Junos Version: For Juniper Mist Wired Assurance to function correctly, the switch must be running a supported Junos version. This ensures compatibility with Mist's cloud management and AI capabilities.

Factory-Default State or Zeroize Command: The switch must boot from a factory-default state, or you can use therequest system zeroizecommand to reset its configuration. This is essential for seamless onboarding and auto-provisioning.

References:

Juniper Mist Wired Assurance Documentation

Wired Assurance Guide

Real-time Assessment: Juniper Mist's Radio Resource Management (RRM) builds the channel plan based on real-time network assessments. It dynamically adjusts to changing conditions in the RF environment, ensuring optimal performance by continuously monitoring factors such as interference, client distribution, and usage patterns.

Automatic Tuning: RRM tuning happens automatically. Mist AI leverages reinforcement learning to continually optimize RF settings without manual intervention, adjusting channels, power levels, and other parameters in real-time to maintain optimal network performance.

References:

Understanding Radio Resource Management | Juniper Networks

Radio Management | Mist | Juniper Networks

Identify the Changes: Radio Resource Management (RRM) changes and their timings.

RRM Changes:

Channel and power settings based on long-term statistics.

RF template changes to channel width.

Changes triggered by SSID scheduling.

Changes triggered by DFS events.

Timing of Changes:

Long-term RRM changes to channel and power settings are typically scheduled once a day to avoid disrupting network performance.

Conclusion:

Channel and power settings across a site based on long-term statistics and baselines are made once a day between 2:00 AM and 3:00 AM local time.

References:

Mist Documentation on RRM: Mist Documentation

When several APs fail to update to the latest firmware during a scheduled downtime, Marvis categorizes this issue as a "non-compliant" action.

This categorization indicates that some APs are not adhering to the intended firmware version policy, which could potentially affect network performance or security.

The non-compliant Marvis Action provides administrators with the necessary information to identify and rectify the issue, ensuring all APs are updated as required.

Reference: Juniper Networks documentation on Marvis Actions and firmware compliance.

Time Zone Importance: Setting the correct time zone for a Mist site ensures that all events and logs are timestamped accurately according to the local time of the site. This is crucial for effective monitoring and troubleshooting.

Facilitation of Troubleshooting: By aligning event timestamps with the local time, network administrators can correlate events more easily with specific incidents reported by users, thereby simplifying the troubleshooting process.

References:

Juniper Networks Documentation

Mist Cloud Communication Protocol: The Mist cloud platform uses HTTPS (Hypertext Transfer Protocol Secure) to communicate with connected access points. This ensures that the data sent and received is encrypted and secure, adhering to modern security standards​(Juniper Networks)​​(CertEnsure)​.

Security and Reliability: Using HTTPS provides a secure channel over which configuration changes, updates, and monitoring data can be safely transmitted between the Mist cloud and the access points. This protocol is widely accepted and trusted for secure communications over the internet.

Incorrect Options:

MQTT: While MQTT is a lightweight messaging protocol often used in IoT, it is not the protocol used by Mist cloud for AP communication.

SSH: Secure Shell (SSH) is primarily used for secure remote command-line access and not for the primary communication between Mist cloud and APs.

PPTP: Point-to-Point Tunneling Protocol (PPTP) is used for implementing VPNs and is not relevant to the communication between Mist cloud and access points.

References:

Juniper Networks Documentation: Mist Cloud Communication

To ensure that you receive alerts when a switch interface goes down, you need to enable the Up/Down Port Alerts setting for the specific interface.

This setting can be configured by navigating to the switch within the Mist UI and modifying the port configuration. Enabling this setting ensures that any changes in the port status, such as going down, will trigger an alert.

This is critical for proactive network monitoring and to promptly address any connectivity issues.

Reference: Juniper Networks documentation on configuring port alerts within the Mist UI.

Service Level Expectations (SLEs): In Mist's SLE dashboard, SLEs are shown as a percentage of success. This indicates how well the network is meeting the predefined performance metrics, such as throughput, capacity, and coverage​(CertsHero)​.

Classifiers: Classifiers, which help in diagnosing issues by breaking down SLEs into specific causes, are also displayed as a percentage of success. This unified view aids in quickly identifying areas that need improvement and ensures consistent monitoring​(CertsHero)​.

References:

Juniper Networks Documentation

Marvis Actions is a component of the Mist AI platform that provides a dashboard highlighting actionable items. This dashboard is designed to offer insights and recommendations based on the analysis performed by Marvis AI.

The focus of Marvis Actions is to present users with clear, actionable steps that can improve network performance, resolve issues, and enhance the overall user experience.

By consolidating relevant information and suggested actions, Marvis Actions helps network administrators efficiently address network challenges and optimize operations.

Reference: Juniper Networks documentation on Marvis Actions and its role within the Mist AI ecosystem.

Enable Two-Factor Authentication (2FA): Adding 2FA to administrator logins significantly enhances security by requiring a second form of verification in addition to the password, making unauthorized access more difficult.

Enable a Password Policy: Implementing a strong password policy ensures that passwords meet certain complexity and length requirements, reducing the risk of brute force attacks.

References:

Juniper Networks Documentation

Agile Feature Updates and Bug Fixes: Juniper Mist's microservices architecture allows for rapid development and deployment of new features and bug fixes. This agility ensures that improvements and fixes can be rolled out continuously without impacting the entire system​(CertsHero)​.

Increased Scalability: The microservices approach enables horizontal scaling, where individual services can be scaled independently based on demand. This allows the system to handle increased load efficiently​(CertsHero)​.

Implementation of Machine Learning: Juniper Mist's architecture leverages machine learning within its microservices to provide intelligent network management and predictive analytics. This enhances the capability of the system to optimize performance and troubleshoot issues proactively​(Juniper Networks)​​(CertsHero)​.

References:

Juniper Networks Documentation

Wayfinding: User Engagement in Mist AI includes wayfinding services that help users navigate through complex environments such as large buildings or campuses. This feature uses real-time location data to guide users to their destinations.

Implementation: Wayfinding leverages Mist's BLE (Bluetooth Low Energy) technology and virtual beacons to provide precise indoor navigation and enhance the user experience.

References:

Juniper Networks Documentation

Mist AI uses reinforcement learning in its Radio Resource Management (RRM) service. This approach allows the system to dynamically optimize the performance of the wireless network by adjusting various radio parameters. The RRM service continuously learns and adapts based on network conditions, user behavior, and environmental factors to ensure optimal performance and reliability.

References:

Juniper Mist AI Overview

Mist AI Technology