# StatsD — Simple Daemon for Aggregating Application Metrics

> StatsD is a lightweight Node.js daemon that listens for UDP metrics from your applications, aggregates them over flush intervals, and forwards them to backends like Graphite, InfluxDB, or Datadog.

## Install

Save as a script file and run:

# StatsD — Simple Daemon for Aggregating Application Metrics

## Quick Use
```bash
# Clone and run
git clone https://github.com/statsd/statsd.git
cd statsd
node stats.js exampleConfig.js

# Send a counter from any language
echo "deploys.myapp:1|c" | nc -u -w0 127.0.0.1 8125
```

## Introduction
StatsD, originally created at Etsy, solves a simple problem: application code should be able to emit metrics with a single line over UDP, with no performance overhead. The daemon collects those fire-and-forget packets, aggregates counters, timers, and gauges, then flushes summaries to a time-series backend.

## What StatsD Does
- Listens on a UDP (or TCP) port for lightweight metric packets
- Aggregates counters, timers, gauges, histograms, and sets over configurable flush intervals
- Forwards aggregated data to pluggable backends (Graphite, InfluxDB, Datadog, and more)
- Supports metric namespacing and tagging for organized dashboards
- Handles high-throughput metric streams with minimal resource usage

## Architecture Overview
StatsD runs as a single Node.js process. Applications send short text-encoded metric lines over UDP. A flush timer fires at a configurable interval (default 10 seconds), computing sums, rates, percentiles, and other aggregates. Results are written to one or more backend modules. Because the protocol is UDP and fire-and-forget, instrumentation adds near-zero latency to application code.

## Self-Hosting & Configuration
- Requires Node.js; start with a JSON config file specifying port and backend
- Default port 8125 (UDP); optionally enable TCP for reliable delivery
- Configure flush interval, percentile thresholds, and key prefix in the config file
- Add backend plugins for Graphite, InfluxDB, Elasticsearch, or cloud services
- Run behind a process manager like systemd or PM2 for production use

## Key Features
- Near-zero overhead metric emission via UDP from any language
- Broad client library ecosystem (Python, Ruby, Go, Java, PHP, and more)
- Pluggable backend architecture for any time-series store
- Built-in percentile calculations for timer metrics
- Battle-tested at Etsy and adopted across the industry

## Comparison with Similar Tools
- **Prometheus** — pull-based model with richer querying; StatsD is push-based and simpler to instrument
- **Telegraf** — InfluxData's agent that can replace StatsD with a StatsD input plugin plus many other inputs
- **Datadog Agent** — commercial agent with StatsD-compatible interface and managed backend
- **OpenTelemetry Collector** — vendor-neutral telemetry pipeline; broader scope but more complex to set up

## FAQ
**Q: Why UDP instead of TCP?**
A: UDP means the application never blocks on metric delivery. If the StatsD daemon is down, packets are silently dropped with no impact on the app.

**Q: Can StatsD handle high cardinality metrics?**
A: StatsD works best with bounded metric names. For high-cardinality tagging, consider pairing it with a backend that supports tags natively.

**Q: Is the Node.js implementation a bottleneck?**
A: For most workloads, a single Node.js process handles thousands of metrics per second. Alternative implementations in Go or C exist for extreme throughput.

**Q: How do I visualize StatsD data?**
A: Forward to Graphite and use Grafana, or send to InfluxDB, Datadog, or any supported backend with its own dashboard.

## Sources
- https://github.com/statsd/statsd
- https://github.com/statsd/statsd/blob/master/docs/metric_types.md

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Source: https://tokrepo.com/en/workflows/asset-cd699ca2
Author: Script Depot