What is responsible for Mist AI data collection and analysis across the wireless, wired, and WAN domains?
Correct Answer: A
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). References:- Juniper Mist AI Cloud Architecture and Operations Guide- Juniper Mist AI Fundamentals Study Guide- Juniper Mist Predictive Analytics and Correlation Engine Overview
Question 42
Which statement about microservices is correct?
Correct Answer: A
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. References:- Juniper Mist Cloud Architecture and Operations Guide- Juniper Mist Cloud Fundamentals Study Guide- Juniper Mist AI and Microservices Overview
Question 43
Which two components make up a self-driving AI network? (Choose two.)
Correct Answer: A,B
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). Reference:HPE Juniper Networking Self-Driving Network Overview
Question 44
Which data format is used for exchanging data with the Juniper Mist REST API?
Correct Answer: C
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. Reference:Juniper Mist RESTful API Overview, Mist API Introduction, Mist Automation Guide
Question 45
How do Wireless Assurance SLEs help administrators troubleshoot?
Correct Answer: D
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 experience and 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 benchmarks that simplify troubleshooting, improve performance visibility, and shorten mean time to repair (MTTR). References:- Juniper Mist Wireless Assurance and SLEs Overview- Juniper Mist AI Operations and Analytics Guide- Juniper Mist Cloud Documentation on Service Level Expectations
