Monitor a remote Linux server over SSH without installing heavy monitoring infrastructure.
Export system metrics to Prometheus or InfluxDB for visualization in Grafana dashboards.
Track CPU, memory, and disk usage of Docker containers alongside host processes in one view.
Query system stats programmatically via REST API or Python library for custom automation scripts.
Requires InfluxDB and Prometheus services running; Docker/LXC setup needed for remote monitoring features.
Glances is a system monitoring tool, an alternative to the classic top and htop commands, that gives you a real-time view of what is happening on your computer or server. It shows CPU usage, memory consumption, disk activity, network traffic, running processes, temperatures, fan speeds, and more, all in a single dashboard that fits your terminal window and automatically adapts to the available screen size. What sets Glances apart from basic tools like top is its range of operation modes. In standalone mode, you run it locally and see your own machine's stats. In client/server mode, you can point it at a remote machine over the network and monitor it from your terminal. It also has a web interface mode where it starts a small HTTP server and displays the same dashboard in any browser at the machine's IP address. A RESTful API comes included, so you can query stats programmatically from other tools or scripts. Recent versions also expose an MCP server endpoint, which lets AI assistants query system state directly. Beyond display, Glances can export its data continuously to external systems, including time-series databases like InfluxDB and Prometheus, CSV files, and directly to standard output in JSON format, which makes it useful as a data source for dashboards like Grafana or for automated alerting systems. It supports monitoring Docker and LXC containers alongside regular processes. You would use Glances when you want a quick, comprehensive view of what a Linux, macOS, BSD, or Windows system is doing, especially over SSH on a remote server where you want more information than top provides without setting up a full monitoring stack. It installs via pip, runs as a Python application, has a plugin architecture for adding custom metrics, and can also be used as a Python library in your own code.
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