To review and troubleshoot the roaming activity of a specific client within a Juniper Mist environment, administrators rely on the conversational and analytical power of the Marvis Virtual Network Assistant (D) and its underlying Marvis Query Language (C). While other Marvis components like Actions focus on organization-wide health and Minis focus on synthetic testing, the VNA and MQL are specifically designed for deep-dive investigations into individual client experiences.
The Marvis Virtual Network Assistant (VNA) serves as the primary interface for this task. It allows an administrator to interact with the Mist AI using natural language. By typing a request such as "Troubleshoot client [Client Name]" or "How was the roaming for [Client Name]?", Marvis VNA aggregates all relevant telemetry data—including signal strength (RSSI), AP transitions, and authentication timings—into a simplified, human-readable summary. It provides a visual timeline of where the client moved and whether each roam was successful, slow, or failed.
Behind the scenes, these natural language requests are often converted into or powered by the Marvis Query Language (MQL). MQL is a structured way to query the Mist Graph API. For specific roaming reviews, the ROAMINGOF clause is used to filter the massive Mist data set for events related only to that client's mobility. For example, a query like roaming of "User-1" during last 24 hours will return a detailed data set showing the "From AP" and "To AP" details, the delta in signal strength during the handoff, and any associated latency.
By using these two features together, administrators can distinguish between a "sticky client" (one that refuses to roam despite a better signal being available) and a "coverage hole" (where the signal drops too low before a new AP is detected). This AI-driven approach eliminates the need for manual packet captures or log parsing, significantly reducing the Mean Time to Repair (MTTR) for mobility-related issues.
