Nginx and Apache Druid 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 send JSON-formatted metrics to Apache Druid over HTTP, enabling real-time ingestion for analytical queries on high-volume time-series data.

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.

Apache Druid

This configuration uses Telegraf’s HTTP output plugin with json data format to send metrics directly to Apache Druid, a real-time analytics database designed for fast, ad hoc queries on high-ingest time-series data. Druid supports ingestion via HTTP POST to various components like the Tranquility service or native ingestion endpoints. The JSON format is ideal for structuring Telegraf metrics into event-style records for Druid’s columnar and time-partitioned storage engine. Druid excels at powering interactive dashboards and exploratory queries across massive datasets, making it an excellent choice for real-time observability and monitoring analytics when integrated with Telegraf.

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"

Apache Druid

[[outputs.http]]
  ## Druid ingestion endpoint (e.g., Tranquility, HTTP Ingest, or Kafka REST Proxy)
  url = "http://druid-ingest.example.com/v1/post"

  ## Use POST method to send events
  method = "POST"

  ## Data format for Druid ingestion (expects JSON format)
  data_format = "json"

  ## Optional headers (may vary depending on Druid setup)
  # [outputs.http.headers]
  #   Content-Type = "application/json"
  #   Authorization = "Bearer YOUR_API_TOKEN"

  ## Optional timeout and TLS settings
  timeout = "10s"
  # tls_ca = "/path/to/ca.pem"
  # tls_cert = "/path/to/cert.pem"
  # tls_key = "/path/to/key.pem"
  # insecure_skip_verify = false

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.

Apache Druid

1. Real-Time Application Monitoring Dashboard: Use Telegraf to collect metrics from application servers and send them to Druid for immediate analysis and visualization in dashboards. Druid’s low-latency querying allows users to interactively explore system behavior in near real-time.

2. Security Event Aggregation: Aggregate and forward security-related metrics such as failed logins, port scans, or process anomalies to Druid. Analysts can build dashboards to monitor threat patterns and investigate incidents with millisecond-level granularity.

3. IoT Device Analytics: Collect telemetry from edge devices via Telegraf and send it to Druid for fast, scalable processing. Druid’s time-partitioned storage and roll-up capabilities are ideal for handling billions of small JSON events from sensors or gateways.

4. Web Traffic Behavior Exploration: Use Telegraf to capture web server metrics (e.g., requests per second, latency, error rates) and forward them to Druid. This enables teams to drill down into user behavior by region, device, or request type with subsecond query performance.

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