Installing and Localizing Netdata: A Real‑Time Linux Performance Monitoring Tool
This article explains how to install Netdata, a web‑based real‑time Linux performance monitoring tool, and provides a step‑by‑step guide to applying a Chinese localization script, including required dependencies, installation commands, and an overview of its key monitoring capabilities.
Netdata is a real‑time performance monitoring tool for Linux systems that presents metrics such as CPU, memory, disk I/O, and network activity through a fast, Flash‑free web interface built with Bootstrap.
Because Netdata does not ship with an official Chinese version, the author created a simple localization by using a provided script and a forked repository.
The installation process begins with installing the same dependencies as the original version, then cloning the forked repository:
https://github.com/Fhaohaizi/netdata
Next, run the Chinese installer script netdata-installer-zh.sh , after which the Netdata service automatically restarts and the web UI displays the localized strings.
For reference, the original installation commands are also shown:
curl -Ss 'https://raw.githubusercontent.com/firehol/netdata-demo-site/master/install-required-packages.sh' >/tmp/kickstart.sh && bash /tmp/kickstart.sh -i netdata
curl -Ss 'https://raw.githubusercontent.com/firehol/netdata-demo-site/master/install-required-packages.sh' >/tmp/kickstart.sh && bash /tmp/kickstart.sh -i netdata-all
git clone https://github.com/firehol/netdata.git --depth=1
cd netdata
# install
./netdata-installer.sh
service netdata start
After installation, the dashboard can be accessed at http:// ip :19999/ , where users can view real‑time graphs.
Netdata’s advantages include a beautiful Bootstrap UI, high efficiency because it is written in C (typically using only about 2 % of a single CPU core), zero‑configuration, and zero external dependencies, as it serves its own static web files.
The tool can monitor a wide range of metrics, such as:
CPU usage, interrupts, soft‑interrupts, and frequency per core
RAM, swap, and kernel memory usage (including KSM and deduplication)
Disk I/O per device (bandwidth, operations, utilization)
IPv4 network statistics (packets, errors, fragmentation) and detailed TCP/UDP/ broadcast/ multicast data
Netfilter/iptables firewall events
Process activity (running, blocked, forks, threads)
NFS file‑server activity
Network service quality metrics
Application‑level statistics grouped by process tree (CPU, memory, disk I/O, threads, sockets, etc.)
Apache web‑server status (v2.2, v2.4)
MySQL database metrics across multiple servers (bandwidth, queries/s, locks, temporary tables, connections, binary logs, InnoDB engine details)
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