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nicolargo/glances

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31,726 stars·1,683 forks·Python·other·1 viewnicolargo.github.io/glances↗

Glances

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Features

  • Performance Monitoring - Tracking real-time resource usage and health metrics across diverse operating systems to identify bottlenecks and maintain overall infrastructure stability.
  • System Health Monitors - Track resource usage and health metrics across multiple operating systems to identify bottlenecks and maintain stability in diverse computing environments.
  • System Resource Monitors - A command-line tool that tracks real-time resource usage and hardware health metrics across diverse operating systems and computing environments.
  • Telemetry Exporters - Sending collected system statistics to external databases or monitoring tools for long-term storage and detailed analysis of historical trends.
  • Remote Monitoring Dashboards - Accessing live performance data through a web interface to monitor system health from any device without requiring direct terminal access.
  • Telemetry Exporters - A data collection agent that streams system performance statistics to external databases and monitoring tools for long-term historical analysis.
  • Data Export Pipelines - Pushes collected system statistics to external databases for long-term storage and historical analysis.
  • System Abstraction Layers - Translates diverse operating system kernel calls into a consistent set of performance metrics.
  • Web-Based Dashboards - View live performance data through a browser-based interface to track system health from any device without needing direct access to a command line terminal.
  • Infrastructure Dashboards - A web-based interface that provides remote access to live infrastructure metrics from any device without requiring direct terminal access.
  • Real-Time Data Streaming - Streams real-time performance data to browser clients via standard network protocols.
  • Glances is a cross-platform system monitoring tool designed to track real-time resource usage and hardware health metrics across diverse computing environments. It functions as a command-line utility that provides a unified view of system performance, identifying bottlenecks and maintaining infrastructure stability through a consistent abstraction layer that translates kernel calls into actionable data.

    The project distinguishes itself through its distributed capabilities, offering a web-based interface that enables remote access to live performance metrics from any device without requiring direct terminal access. It also operates as a telemetry data exporter, utilizing an export-driven pipeline to stream collected statistics to external databases and monitoring tools for long-term historical analysis.

    The system supports a modular architecture that allows for extensible data collection through independent scripts. It facilitates remote monitoring by maintaining persistent network connections between lightweight data providers and centralized management interfaces.