[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"workflow-asset-cd699ca2":3,"seo:featured-workflow:cd699ca2-4eca-11f1-9bc6-00163e2b0d79:en":83,"workflow-related-asset-cd699ca2-cd699ca2-4eca-11f1-9bc6-00163e2b0d79":84},{"id":4,"uuid":5,"slug":6,"title":7,"description":8,"author_id":9,"author_name":10,"author_avatar":11,"token_estimate":12,"time_saved":12,"model_used":13,"fork_count":12,"vote_count":12,"view_count":12,"parent_id":12,"parent_uuid":13,"lang_type":14,"steps":15,"tags":22,"has_voted":28,"visibility":18,"share_token":13,"is_featured":12,"content_hash":29,"asset_kind":30,"target_tools":31,"install_mode":35,"entrypoint":19,"risk_profile":36,"dependencies":38,"verification":43,"agent_metadata":46,"agent_fit":59,"trust":71,"provenance":80,"created_at":82,"updated_at":82},3612,"cd699ca2-4eca-11f1-9bc6-00163e2b0d79","asset-cd699ca2","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.","8a910e34-3180-11f1-9bc6-00163e2b0d79","Script Depot","https:\u002F\u002Ftokrepo.com\u002Fapple-touch-icon.png",0,"","en",[16],{"id":17,"step_order":18,"title":19,"description":13,"prompt_template":20,"variables":13,"depends_on":21,"expected_output":13},4172,1,"StatsD Metrics Daemon","# StatsD — Simple Daemon for Aggregating Application Metrics\n\n## Quick Use\n```bash\n# Clone and run\ngit clone https:\u002F\u002Fgithub.com\u002Fstatsd\u002Fstatsd.git\ncd statsd\nnode stats.js exampleConfig.js\n\n# Send a counter from any language\necho \"deploys.myapp:1|c\" | nc -u -w0 127.0.0.1 8125\n```\n\n## Introduction\nStatsD, 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.\n\n## What StatsD Does\n- Listens on a UDP (or TCP) port for lightweight metric packets\n- Aggregates counters, timers, gauges, histograms, and sets over configurable flush intervals\n- Forwards aggregated data to pluggable backends (Graphite, InfluxDB, Datadog, and more)\n- Supports metric namespacing and tagging for organized dashboards\n- Handles high-throughput metric streams with minimal resource usage\n\n## Architecture Overview\nStatsD 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.\n\n## Self-Hosting & Configuration\n- Requires Node.js; start with a JSON config file specifying port and backend\n- Default port 8125 (UDP); optionally enable TCP for reliable delivery\n- Configure flush interval, percentile thresholds, and key prefix in the config file\n- Add backend plugins for Graphite, InfluxDB, Elasticsearch, or cloud services\n- Run behind a process manager like systemd or PM2 for production use\n\n## Key Features\n- Near-zero overhead metric emission via UDP from any language\n- Broad client library ecosystem (Python, Ruby, Go, Java, PHP, and more)\n- Pluggable backend architecture for any time-series store\n- Built-in percentile calculations for timer metrics\n- Battle-tested at Etsy and adopted across the industry\n\n## Comparison with Similar Tools\n- **Prometheus** — pull-based model with richer querying; StatsD is push-based and simpler to instrument\n- **Telegraf** — InfluxData's agent that can replace StatsD with a StatsD input plugin plus many other inputs\n- **Datadog Agent** — commercial agent with StatsD-compatible interface and managed backend\n- **OpenTelemetry Collector** — vendor-neutral telemetry pipeline; broader scope but more complex to set up\n\n## FAQ\n**Q: Why UDP instead of TCP?**\nA: 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.\n\n**Q: Can StatsD handle high cardinality metrics?**\nA: StatsD works best with bounded metric names. For high-cardinality tagging, consider pairing it with a backend that supports tags natively.\n\n**Q: Is the Node.js implementation a bottleneck?**\nA: For most workloads, a single Node.js process handles thousands of metrics per second. Alternative implementations in Go or C exist for extreme throughput.\n\n**Q: How do I visualize StatsD data?**\nA: Forward to Graphite and use Grafana, or send to InfluxDB, Datadog, or any supported backend with its own dashboard.\n\n## Sources\n- https:\u002F\u002Fgithub.com\u002Fstatsd\u002Fstatsd\n- 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