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QNetwork is a Windows desktop application developed by Code-iX for live per-process network traffic monitoring, currently available at version 1.0.1, with two versions having been released to date. Positioned within the network monitoring and system diagnostics category, the software is designed to give users detailed, real-time visibility into how individual processes on a Windows machine consume network bandwidth. It uses ETW (Event Tracing for Windows) kernel tracing as its data collection mechanism, which enables accurate per-process traffic accounting; because of this approach, administrator rights are required to run the per-process collection features. The tool displays active process totals, inbound and outbound traffic rates, cumulative session totals, recorded traffic peaks, and currently active connections, allowing users to identify which applications are generating network activity at any given moment. A built-in 60-second traffic history chart visualizes recent network behavior and supports process-level grouping and filtering, making it possible to focus on specific applications or compare multiple processes side by side. Additional functionality includes CSV export for saving monitoring data for later analysis or reporting, minimization to the system tray so the monitor can run unobtrusively in the background, adapter filtering to narrow observation to particular network interfaces, and configurable alert thresholds that notify users when traffic exceeds defined limits. Typical use cases include diagnosing unexpected bandwidth consumption, identifying processes responsible for heavy uploads or downloads, verifying the network behavior of installed software, troubleshooting connectivity issues, and general performance observation for administrators, developers, and technically inclined end users. By combining kernel-level ETW tracing with a focused desktop interface, QNetwork serves as a practical utility for anyone needing immediate, process-granular insight into network activity on Windows systems without relying on more complex enterprise monitoring solutions.
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