StatsD and SigNoz Integration

Input and output integration overview

<p>The StatsD input plugin captures metrics from a StatsD server by running a listener service in the background, allowing for comprehensive performance monitoring and metric aggregation.</p>

<p>This configuration turns any Telegraf agent into a Remote Write publisher for SigNoz, streaming rich metrics straight into the SigNoz backend with a single URL change.</p>

Integration details

StatsD

<p>The StatsD input plugin is designed to gather metrics from a StatsD server by running a backgrounded StatsD listener service while Telegraf is active. This plugin leverages the format of the StatsD messages as established by the original Etsy implementation, which allows for various types of metrics including gauges, counters, sets, timings, histograms, and distributions. The capabilities of the StatsD plugin extend to parsing tags and extending the standard protocol with features that accommodate InfluxDB’s tagging system. It can handle messages sent via different protocols (UDP or TCP), manage multiple metric metrics effectively, and offers advanced configurations for optimal metric handling such as percentiles calculation and data transformation templates. This flexibility empowers users to track application performance comprehensively, making it an essential tool for robust monitoring setups.</p>

SigNoz

<p>SigNoz is an open source observability platform that stores metrics, traces, and logs. When you deploy SigNoz, its <strong>signoz-otel-collector-metrics</strong> service exposes a Prometheus Remote Write receiver (default <strong>:13133/api/v1/write</strong>). By configuring Telegraf’s Prometheus plugin to point at this endpoint, you can push any Telegraf collected metrics, SNMP counters, cloud services, or business KPIs—directly into SigNoz. The plugin natively serializes metrics in the Remote Write protobuf format, supports external labels, metadata export, retries, and TLS or bearer-token auth, so it fits zero-trust and multi-tenant SigNoz clusters. Inside SigNoz, the data lands in ClickHouse tables that back Metrics Explorer, alert rules, and unified dashboards. This approach lets organizations unify Prometheus and OTLP pipelines, enables long-term retention powered by ClickHouse compression, and avoids vendor lock-in while retaining PromQL-style queries.</p>

Configuration

StatsD

SigNoz

Input and output integration examples

StatsD

<ol> <li> <p><strong>Real-time Application Performance Monitoring</strong>: Utilize the StatsD input plugin to monitor application performance metrics in real-time. By configuring your application to send various metrics to a StatsD server, teams can leverage this plugin to analyze performance bottlenecks, track user activity, and ensure resource optimization dynamically. The combination of historical and real-time metrics allows for proactive troubleshooting and enhances the responsiveness of issue resolution processes.</p> </li> <li> <p><strong>Tracking User Engagement Metrics in Web Applications</strong>: Use the StatsD plugin to gather user engagement statistics, such as page views, click events, and interaction times. By sending these metrics to the StatsD server, businesses can derive valuable insights into user behavior, enabling them to make data-driven decisions to improve user experience and interface design based on quantitative feedback. This can significantly enhance the effectiveness of marketing strategies and product development efforts.</p> </li> <li> <p><strong>Infrastructure Health Monitoring</strong>: Deploy the StatsD plugin to monitor the health of your server infrastructure by tracking metrics such as resource utilization, server response times, and network performance. With this setup, DevOps teams can gain detailed visibility into system performance, effectively anticipating issues before they escalate. This enables a proactive approach to infrastructure management, minimizing downtimes and ensuring optimal service delivery.</p> </li> <li> <p><strong>Creating Comprehensive Service Dashboards</strong>: Integrate StatsD with visualization tools to create comprehensive dashboards that reflect the status and health of services across an architecture. For instance, combining data from multiple services logged through StatsD can transform raw metrics into actionable insights, showcasing system performance trends over time. This capability empowers stakeholders to maintain oversight and drive decisions based on visualized data sets, enhancing overall operational transparency.</p> </li> </ol>

SigNoz

<ol> <li> <p><strong>Multi-Cluster Federated Monitoring</strong>: Drop a Telegraf DaemonSet into each Kubernetes cluster, tag metrics with <code>cluster=&lt;name&gt;</code>, and Remote Write them to a central SigNoz instance. Ops teams get a single PromQL window across prod, staging, and edge clusters without running Thanos sidecars.</p> </li> <li> <p><strong>Factory-Floor Edge Gateway</strong>: A rugged Intel NUC on the shop floor runs Telegraf to scrape Modbus PLCs and environmental sensors. It batches readings every 5 seconds and pushes them over an intermittent 4G link to SigNoz SaaS. ClickHouse compression keeps costs low while AI-based outlier detection in SigNoz flags overheating motors before failure.</p> </li> <li> <p><strong>SaaS Usage Metering</strong>: Telegraf runs alongside each micro-service, exporting per-tenant counters (<code>api_calls</code>, <code>gigabytes_processed</code>). Remote Write streams the data to SigNoz where a scheduled ClickHouse materialized view aggregates usage for monthly billing—no separate metering stack required.</p> </li> <li> <p><strong>Autoscaling Feedback Loop</strong>: Combine Telegraf’s Kubernetes input with the Remote Write output to publish granular pod CPU and queue-length metrics into SigNoz. A custom SigNoz alert fires when P95 latency breaches 200 ms and a GitOps controller reads that alert to trigger a HorizontalPodAutoscaler tweak—closing the loop between observability and automation.</p> </li> </ol>

Feedback

Thank you for being part of our community! If you have any general feedback or found any bugs on these pages, we welcome and encourage your input. Please submit your feedback in the InfluxDB community Slack.