ActiveMQ and Elasticsearch Integration

Input and output integration overview

<p>The ActiveMQ Input Plugin collects metrics from the ActiveMQ message broker through its Console API, providing insights into the performance and status of message queues, topics, and subscribers.</p>

<p>The Telegraf Elasticsearch Plugin seamlessly sends metrics to an Elasticsearch server. The plugin handles template creation and dynamic index management, and supports various Elasticsearch-specific features to ensure data is formatted correctly for storage and retrieval.</p>

Integration details

ActiveMQ

<p>The ActiveMQ Input Plugin interfaces with the ActiveMQ Console API to gather metrics related to queues, topics, and subscribers. ActiveMQ, a widely-used open-source message broker, supports various messaging protocols and provides a robust Web Console for management and monitoring. This plugin allows users to track essential metrics including queue sizes, consumer counts, and message counts across different ActiveMQ entities, thereby enhancing observability within messaging systems. Users can configure various parameters such as the WebConsole URL and basic authentication credentials to tailor the plugin to their environment. The metrics collected can be used for monitoring the health and performance of messaging applications, facilitating proactive management and troubleshooting.</p>

Elasticsearch

<p>This plugin writes metrics to Elasticsearch, a distributed, RESTful search and analytics engine capable of storing large amounts of data in near real-time. It is designed to handle Elasticsearch versions 5.x through 7.x and utilizes its dynamic template features to manage data type mapping properly. The plugin supports advanced features such as template management, dynamic index naming, and integration with OpenSearch. It also allows configurations for authentication and health monitoring of the Elasticsearch nodes.</p>

Configuration

ActiveMQ

Elasticsearch

Input and output integration examples

ActiveMQ

<ol> <li> <p><strong>Proactive Queue Monitoring</strong>: Use the ActiveMQ plugin to monitor queue sizes in real-time for a high-volume trading application. This implementation allows teams to receive alerts when queue sizes exceed a certain threshold, enabling rapid response to potential downtime caused by backlogs, thereby ensuring continuous availability of trading operations.</p> </li> <li> <p><strong>Performance Baselines and Anomaly Detection</strong>: Integrate this plugin with machine learning frameworks to establish performance baselines for message throughput. By analyzing historical data collected through this plugin, teams can flag anomalies in processing rates, leading to quicker identification of issues impacting service reliability and performance.</p> </li> <li> <p><strong>Cross-Messaging System Analytics</strong>: Combine metrics from ActiveMQ with those from other messaging systems in a centralized dashboard. Users can visualize and compare performance data, such as enqueue and dequeue rates, providing valuable insights into the overall messaging architecture and assisting in optimizing the message flow between different brokers.</p> </li> <li> <p><strong>Subscriber Performance Insights</strong>: Leverage the subscriber metrics collected by this plugin to analyze behavior patterns and optimize configuration for consumer applications. Understanding metrics such as dispatched queue size and counter values can guide adjustments to improve processing efficiency and resource allocation.</p> </li> </ol>

Elasticsearch

<ol> <li> <p><strong>Time-based Indexing</strong>: Use this plugin to store metrics in Elasticsearch to index each metric based on the time collected. For example, CPU metrics can be stored in a daily index named<code>telegraf-2023.01.01</code>, allowing easy time-based queries and retention policies.</p> </li> <li> <p><strong>Dynamic Templates Management</strong>: Utilize the template management feature to automatically create a custom template tailored to your metrics. This allows you to define how different fields are indexed and analyzed without manually configuring Elasticsearch, ensuring an optimal data structure for querying.</p> </li> <li> <p><strong>OpenSearch Compatibility</strong>: If you are using AWS OpenSearch, you can configure this plugin to work seamlessly by activating compatibility mode, ensuring your existing Elasticsearch clients remain functional and compatible with newer cluster setups.</p> </li> </ol>

Feedback

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