Nginx and DuckDB 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 enables Telegraf to write structured metrics into DuckDB using SQLite-compatible SQL connections, supporting lightweight local analytics and offline metric analysis.

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.

DuckDB

Use the Telegraf SQL plugin to write metrics into a local DuckDB database. DuckDB is an in-process OLAP database designed for efficient analytical queries on columnar data. Although it does not provide a traditional client-server interface, DuckDB can be accessed via SQLite-compatible drivers in embedded mode. This allows Telegraf to store time series metrics in DuckDB using SQL, enabling powerful analytics workflows using familiar SQL syntax, Jupyter notebooks, or integration with data science tools like Python and R. DuckDB’s columnar storage and vectorized execution make it ideal for compact and high-performance metric archives.

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"

DuckDB

[[outputs.sql]]
  ## Use the SQLite driver to connect to DuckDB via Go's database/sql
  driver = "sqlite3"

  ## DSN should point to the DuckDB database file
  dsn = "file:/var/lib/telegraf/metrics.duckdb"

  ## SQL INSERT statement with placeholders for metrics
  table_template = "INSERT INTO metrics (timestamp, name, value, tags) VALUES (?, ?, ?, ?)"

  ## Optional: manage connection pooling
  # max_open_connections = 1
  # max_idle_connections = 1
  # conn_max_lifetime = "0s"

  ## DuckDB does not require TLS or authentication by default

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.

DuckDB

1. Embedded Metric Warehousing for Notebooks: Write metrics to a local DuckDB file from Telegraf and analyze them in Jupyter notebooks using Python or R. This workflow supports reproducible analytics, ideal for data science experiments or offline troubleshooting.

2. Batch Time-Series Processing on the Edge: Use Telegraf with DuckDB on edge devices to log metrics locally in SQL format. The compact storage and fast analytical capabilities of DuckDB make it ideal for batch processing and low-bandwidth environments.

3. Exploratory Querying of Historical Metrics: Accumulate system metrics over time in DuckDB and perform exploratory data analysis (EDA) using SQL joins, window functions, and aggregates. This enables insights that go beyond what typical time-series dashboards provide.

4. Self-Contained Metric Snapshots: Use DuckDB as a portable metrics archive by shipping .duckdb files between systems. Telegraf can collect and store data in this format, and analysts can later load and query it using the DuckDB CLI or integrations with tools like Tableau and Apache Arrow.

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.