Supervisor and MariaDB Integration

Input and output integration overview

<p>This plugin gathers information about processes running under Supervisor using the XML-RPC API.</p>

<p>This plugin writes metrics from Telegraf directly into MariaDB using parameterized SQL INSERT statements, offering a flexible way to store metrics in structured, relational tables.</p>

Integration details

Supervisor

<p>The Supervisor plugin for Telegraf is designed to collect metrics about processes managed by the Supervisor process control system using its XML-RPC API. The plugin is able to track various metrics, including process states and uptime, and provides options for configuring which metrics to collect through include or exclude lists. This integration is particularly useful for monitoring applications running under Supervisor, providing insights into their operational status and performance metrics. A minimum tested Supervisor version is 3.3.2, and it is recommended to secure the HTTP server with basic authentication for better security.</p>

MariaDB

<p>The SQL output plugin in Telegraf enables direct writing of metrics into SQL-compatible databases like MariaDB by executing parameterized SQL statements. With support for the MySQL driver, the plugin seamlessly integrates with MariaDB for reliable, structured metric storage. This setup is ideal for users who prefer SQL-based analytics or want to store metrics alongside business data for unified querying. MariaDB is a community-developed, enterprise-grade fork of MySQL that emphasizes performance, security, and openness. The plugin supports inserting time series metrics into custom schemas, enabling flexible analytics and integrations with BI tools like Metabase or Grafana using SQL connectors.</p>

Configuration

Supervisor

MariaDB

Input and output integration examples

Supervisor

<ol> <li> <p><strong>Centralized Monitoring Dashboard</strong>: Implement this plugin to feed Supervisor metrics directly into a centralized monitoring dashboard, allowing teams to visualize the health and performance of their applications in real-time. This integration enables quick identification of issues, helps track service performance over time, and aids in capacity planning based on observed trends.</p> </li> <li> <p><strong>Alerting for Process Failures</strong>: Utilize the metrics gathered by the Supervisor plugin to create an alerting mechanism that notifies engineers when critical processes go down or enter a fatal state. By setting thresholds in your monitoring system, teams can respond proactively to potential problems, minimizing downtime and ensuring system reliability.</p> </li> <li> <p><strong>Historical Analysis of Process States</strong>: Store the metrics collected over time to analyze process state changes and patterns. By examining historical data, teams can identify recurring issues, track the impact of deployment changes, and optimize resource allocation based on process trends, leading to improved overall system performance.</p> </li> <li> <p><strong>Integration with Incident Management Systems</strong>: Configure the Supervisor plugin to automatically send alerts to incident management systems like PagerDuty or OpsGenie when a process reaches a critical state. This integration streamlines the incident response process, ensuring that the right team members are notified promptly and can take action without delay.</p> </li> </ol>

MariaDB

<ol> <li> <p><strong>Business Intelligence Integration</strong>: Store application performance metrics directly into MariaDB and connect it to BI tools like Metabase or Apache Superset. This setup allows blending of operational data with business KPIs for unified dashboards, enhancing visibility across departments.</p> </li> <li> <p><strong>Compliance Reporting with Historical Metrics</strong>: Use this plugin to log metrics into MariaDB for audit and compliance use cases. The relational model enables precise querying of past performance indicators with timestamped entries, supporting regulatory documentation.</p> </li> <li> <p><strong>Custom Alerting Based on SQL Logic</strong>: Insert metrics into MariaDB and use custom SQL queries to define alert thresholds or conditions. Combined with cron jobs or scheduled scripts, this enables advanced alerting workflows not possible with traditional metric platforms.</p> </li> <li> <p><strong>IoT Sensor Metrics Storage</strong>: Collect sensor data from IoT devices via Telegraf and store it in MariaDB using a normalized schema. This approach is cost-effective and integrates well with existing SQL-based systems for real-time or historical analysis.</p> </li> </ol>

Feedback

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