Fluentd and IoTDB Integration

Input and output integration overview

<p>The Fluentd Input Plugin gathers metrics from Fluentd’s in_monitor plugin endpoint. It provides insights into various plugin metrics while allowing for custom configurations to reduce series cardinality.</p>

<p>This plugin saves Telegraf metrics to an Apache IoTDB backend, supporting session connection and data insertion.</p>

Integration details

Fluentd

<p>This plugin gathers metrics from the Fluentd plugin endpoint provided by the in_monitor plugin. It reads data from the /api/plugin.json resource and allows exclusion of specific plugins based on their type.</p>

IoTDB

<p>Apache IoTDB (Database for Internet of Things) is an IoT native database with high performance for data management and analysis, deployable on the edge and the cloud. Its light-weight architecture, high performance, and rich feature set create a perfect fit for massive data storage, high-speed data ingestion, and complex analytics in the IoT industrial fields. IoTDB deeply integrates with Apache Hadoop, Spark, and Flink, which further enhances its capabilities in handling large scale data and sophisticated processing tasks.</p>

Configuration

Fluentd

IoTDB

Input and output integration examples

Fluentd

<ol> <li><strong>Basic Configuration</strong>: Set up the Fluentd Input Plugin to gather metrics from your Fluentd instance’s monitoring endpoint, ensuring you are able to track performance and usage statistics.</li> <li><strong>Excluding Plugins</strong>: Use the <code>exclude</code> option to ignore specific plugins’ metrics that are not necessary for your monitoring needs, streamlining data collection and focusing on what matters.</li> <li><strong>Custom Plugin ID</strong>: Implement the <code>@id</code> parameter in your Fluentd configuration to maintain a consistent <code>plugin_id</code>, which helps avoid issues with high series cardinality during frequent restarts.</li> </ol>

IoTDB

<ol> <li> <p><strong>Real-Time IoT Monitoring</strong>: Utilize the IoTDB plugin to gather sensor data from various IoT devices and save it in an Apache IoTDB backend, facilitating real-time monitoring of environmental conditions such as temperature and humidity. This use case enables organizations to analyze trends over time and make informed decisions based on historical data, while also utilizing IoTDB’s efficient storage and querying capabilities.</p> </li> <li> <p><strong>Smart Agriculture Data Collection</strong>: Use the IoTDB plugin to collect metrics from smart agriculture sensors deployed in fields. By transmitting moisture levels, nutrient content, and atmospheric conditions to IoTDB, farmers can access detailed insights into optimal planting and watering schedules, thus improving crop yields and resource management.</p> </li> <li> <p><strong>Energy Consumption Analytics</strong>: Leverage the IoTDB plugin to track energy consumption metrics from smart meters across a utility network. This integration enables analytics to identify peaks in usage and predict future consumption patterns, ultimately supporting energy conservation initiatives and improved utility management.</p> </li> <li> <p><strong>Automated Industrial Equipment Monitoring</strong>: Use this plugin to gather operational metrics from machinery in a manufacturing plant and store them in IoTDB for analysis. This setup can help identify inefficiencies, predictive maintenance needs, and operational anomalies, ensuring optimal performance and minimizing unexpected downtimes.</p> </li> </ol>

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.