Syslog and Apache Druid Integration

Input and output integration overview

<p>The Syslog plugin enables the collection of syslog messages from various sources using standard networking protocols. This functionality is critical for environments where systems need to be monitored and logged efficiently.</p>

<p>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.</p>

Integration details

Syslog

<p>The Syslog plugin for Telegraf captures syslog messages transmitted over various protocols such as TCP, UDP, and TLS. It supports both RFC 5424 (the newer syslog protocol) and the older RFC 3164 (BSD syslog protocol). This plugin operates as a service input, effectively starting a service that listens for incoming syslog messages. Unlike traditional plugins, service inputs may not function with standard interval settings or CLI options like <code>--once</code>. It includes options for setting network configurations, socket permissions, message handling, and connection handling. Furthermore, the integration with Rsyslog allows forwarding of logging messages, making it a powerful tool for collecting and relaying system logs in real-time, thus seamlessly integrating into monitoring and logging systems.</p>

Apache Druid

<p>This configuration uses Telegraf’s HTTP output plugin with <code>json</code> 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.</p>

Configuration

Syslog

Apache Druid

Input and output integration examples

Syslog

<ol> <li> <p><strong>Centralized Log Management</strong>: Use the Syslog plugin to aggregate log messages from multiple servers into a central logging system. This setup can help in monitoring overall system health, troubleshooting issues effectively, and maintaining audit trails by collecting syslog data from different sources.</p> </li> <li> <p><strong>Real-Time Alerting</strong>: Integrate the Syslog plugin with alerting tools to trigger real-time notifications when specific log patterns or errors are detected. For example, if a critical system error appears in the logs, an alert can be sent to the operations team, minimizing downtime and performing proactive maintenance.</p> </li> <li> <p><strong>Security Monitoring</strong>: Leverage the Syslog plugin for security monitoring by capturing logs from firewalls, intrusion detection systems, and other security devices. This logging capability enhances security visibility and helps in investigating potentially malicious activities by analyzing the captured syslog data.</p> </li> <li> <p><strong>Application Performance Tracking</strong>: Utilize the Syslog plugin to monitor application performance by collecting logs from various applications. This integration helps in analyzing the application’s behavior and performance trends, thus aiding in optimizing application processes and ensuring smoother operation.</p> </li> </ol>

Apache Druid

<ol> <li> <p><strong>Real-Time Application Monitoring Dashboard</strong>: 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.</p> </li> <li> <p><strong>Security Event Aggregation</strong>: 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.</p> </li> <li> <p><strong>IoT Device Analytics</strong>: 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.</p> </li> <li> <p><strong>Web Traffic Behavior Exploration</strong>: 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.</p> </li> </ol>

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