Nginx and M3DB Integration

Input and output integration overview

The Nginx plugin for Telegraf is designed to collect status metrics from Nginx web servers, providing real-time insights into server operation metrics.

This plugin allows Telegraf to stream metrics to M3DB using the Prometheus Remote Write protocol, enabling scalable ingestion through the M3 Coordinator.

Integration details

Nginx

This plugin gathers status metrics from Nginx. It utilizes the ngx_http_stub_status_module to collect basic metrics related to the server’s performance. The plugin provides valuable insights into active connections, requests handled, and the current state of various metrics. This real-time data is essential for monitoring web server performance and ensuring optimal operations. The configuration allows users to specify the URL for the Nginx status endpoint, set timeouts, and configure TLS settings if necessary.

M3DB

This configuration uses Telegraf’s HTTP output plugin with prometheusremotewrite format to send metrics directly to M3DB through the M3 Coordinator. M3DB is a distributed time series database designed for scalable, high-throughput metric storage. It supports ingestion of Prometheus remote write data via its Coordinator component, which manages translation and routing into the M3DB cluster. This approach enables organizations to collect metrics from systems that aren’t natively instrumented for Prometheus (e.g., Windows, SNMP, legacy systems) and ingest them efficiently into M3’s long-term, high-performance storage engine. The setup is ideal for high-scale observability stacks with Prometheus compatibility requirements.

Configuration

Nginx

[[inputs.nginx]]
  ## An array of Nginx stub_status URI to gather stats.
  urls = ["http://localhost/server_status"]

  ## Optional TLS Config
  # tls_ca = "/etc/telegraf/ca.pem"
  # tls_cert = "/etc/telegraf/cert.pem"
  # tls_key = "/etc/telegraf/key.pem"
  ## Use TLS but skip chain & host verification
  # insecure_skip_verify = false

  ## HTTP response timeout (default: 5s)
  response_timeout = "5s"

M3DB

# Configuration for sending metrics to M3
[outputs.http]
  ## URL is the address to send metrics to
  url = "https://M3_HOST:M3_PORT/api/v1/prom/remote/write"

  ## HTTP Basic Auth credentials
  username = "admin"
  password = "password"

  ## Data format to output.
  data_format = "prometheusremotewrite"

  ## Outgoing HTTP headers
  [outputs.http.headers]
    Content-Type = "application/x-protobuf"
    Content-Encoding = "snappy"
    X-Prometheus-Remote-Write-Version = "0.1.0"

Input and output integration examples

Nginx

1. Web Performance Monitoring: Use the Nginx plugin to gather performance metrics from various Nginx servers across your infrastructure. By visualizing these metrics in real-time dashboards, teams can track performance trends, identify bottlenecks, and enhance the user experience on their web applications. Implementing such monitoring allows businesses to proactively address performance issues before they impact end-users.

2. Load Balancer Monitoring: Integrate this plugin with your load balancers to track the performance of backend Nginx servers. By collecting statistics like ‘active connections’ and ‘requests handled’, your operations team can ensure that traffic is flowing optimally and that no single server is overwhelmed. This proactive approach to load balancing prevents service downtime and enhances user experience.

3. Automated Alerting Systems: Combine the Nginx plugin with alerting services to automatically notify your team when a server’s metrics exceed predefined thresholds. For instance, if the number of active connections is too high, the system can trigger alerts so that corrective actions can be taken immediately, thus maintaining service quality and reliability.

4. Historical Data Analysis: Store the metrics collected by the Nginx plugin in a time-series database to analyze historical performance trends. This analysis can uncover periods of high traffic or poor performance, allowing for data-driven decisions about infrastructure scaling and optimization. By understanding past trends, organizations can better prepare for future demands.

M3DB

1. Large-Scale Cloud Infrastructure Monitoring: Deploy Telegraf agents across thousands of virtual machines and containers to collect metrics and stream them into M3DB through the M3 Coordinator. This provides reliable, long-term visibility with minimal storage overhead and high availability.

2. Legacy System Metrics Ingestion: Use Telegraf to gather metrics from older systems that lack native Prometheus exporters (e.g., Windows servers, SNMP devices) and forward them to M3DB via remote write. This bridges modern observability workflows with legacy infrastructure.

3. Centralized App Telemetry Aggregation: Collect application-specific telemetry using Telegraf’s plugin ecosystem (e.g., exec, http, jolokia) and push it into M3DB for centralized storage and query via PromQL. This enables unified analytics across diverse data sources.

4. Hybrid Cloud Observability: Install Telegraf agents on-prem and in the cloud to collect and remote-write metrics into a centralized M3DB cluster. This ensures consistent visibility across environments while avoiding the complexity of running Prometheus federation layers.

Feedback

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