Graphios
A program to send Nagios performance data to Graphite, StatsD, Librato, and InfluxDB.
What is Graphios?
Graphios is a Python script that forwards performance data from Nagios, Icinga, or Naemon monitoring systems to external time-series databases and metrics platforms like Graphite, StatsD, Librato, and InfluxDB. It solves the problem of integrating traditional monitoring systems with modern graphing and analytics tools, enabling better visualization and long-term trend analysis of infrastructure metrics.
Intermediate to advanced Nagios, Icinga, or Naemon administrators who want to export performance data to graphing systems for visualization and analysis.
Developers choose Graphios because it supports multiple backends simultaneously, offers flexible metric naming through custom variables or automatic service descriptions, and integrates seamlessly with existing Nagios configurations without replacing the monitoring system itself.
Overview
A program to send nagios perf data to graphite (carbon) / statsd / librato / influxdb
Use Cases
Best For
- Sending Nagios perfdata to Graphite for long-term metric storage
- Forwarding monitoring metrics to StatsD for real-time aggregation
- Exporting performance data to InfluxDB for time-series analysis
- Integrating Nagios with Librato for cloud-based metrics visualization
- Using service descriptions for automatic metric naming without custom variables
- Adding a universal prefix to all metrics for multi-source environments
Not Ideal For
- Teams using modern monitoring stacks like Prometheus that natively export metrics without Nagios
- Environments requiring Python 3.x compatibility for future development
- Projects needing real-time, sub-second metric streaming due to file-based batch processing with configurable intervals
- Setups with highly inconsistent plugin output units, as Graphios doesn't handle unit normalization
Pros & Cons
Pros
Simultaneously sends metrics to Graphite, StatsD, Librato, and InfluxDB, enabling integration with diverse graphing systems without replacing Nagios.
Uses Nagios custom variables (_graphiteprefix, _graphitepostfix) or service descriptions to construct hierarchical metric names, offering fine-grained control.
Adapts naming for backends like Librato by omitting hostnames as separate source dimensions, ensuring compatibility with their metrics model.
Allows using service descriptions for metric naming without custom variables, simplifying setup for environments with consistent service labels.
Cons
Only supports Python 2.6 or later, not Python 3.x, which is outdated and limits adoption in modern Python ecosystems.
Requires manual modifications to Nagios.cfg, custom command definitions, and graphios.cfg, making installation error-prone for non-experts.
Relies on moving and processing spool files at intervals (e.g., 15 seconds), which may not scale well for high-volume, low-latency metric streams.
Frequently Asked Questions
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