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.
[References:– Juniper Mist AI Cloud Architecture and Operations Guide– Juniper Mist Predictive Analytics and Correlation Engine (PACE) Documentation– Juniper Mist AI Platform Overview and Study Guide, , ]