AWS Data Firehose and Sumo Logic Integration

Input and output integration overview

<p>This plugin listens for metrics sent via HTTP from AWS Data Firehose in supported data formats, providing real-time data ingestion capabilities.</p>

<p>The Sumo Logic plugin is designed to facilitate the sending of metrics from Telegraf to Sumo Logic’s HTTP Source. By utilizing this plugin, users can analyze their metric data in the Sumo Logic platform, leveraging various output data formats.</p>

Integration details

AWS Data Firehose

<p>The AWS Data Firehose Telegraf plugin is designed to receive metrics from AWS Data Firehose via HTTP. This plugin listens for incoming data in various formats and processes it according to the request-response schema outlined in the official AWS documentation. Unlike standard input plugins that operate on a fixed interval, this service plugin initializes a listener that remains active, waiting for incoming metrics. This allows for real-time data ingestion from AWS Data Firehose, making it suitable for scenarios where immediate data processing is required. Key features include the ability to specify service addresses, paths, and support for TLS connections for secure data transmission. Additionally, the plugin accommodates optional authentication keys and custom tags, enhancing its flexibility in various use cases involving data streaming and processing.</p>

Sumo Logic

<p>This plugin facilitates the transmission of metrics to Sumo Logic’s HTTP Source, employing specified data formats for HTTP messages. Telegraf, which must be version 1.16.0 or higher, can send metrics encoded in several formats, including <code>graphite</code>, <code>carbon2</code>, and <code>prometheus</code>. These formats correspond to different content types recognized by Sumo Logic, ensuring that the metrics are correctly interpreted for analysis. Integration with Sumo Logic allows users to leverage a comprehensive analytics platform, enabling rich visualizations and insights from their metric data. The plugin provides configuration options such as setting URLs for the HTTP Metrics Source, choosing the data format, and specifying additional parameters like timeout and request size, which enhance flexibility and control in data monitoring workflows.</p>

Configuration

AWS Data Firehose

Sumo Logic

Input and output integration examples

AWS Data Firehose

<ol> <li> <p><strong>Real-Time Data Analytics</strong>: Using the AWS Data Firehose plugin, organizations can stream data in real-time from various sources, such as application logs or IoT devices, directly into analytics platforms. This allows data teams to analyze incoming data as it is generated, enabling rapid insights and operational adjustments based on fresh metrics.</p> </li> <li> <p><strong>Profile Access Patterns for Optimization</strong>: By collecting data about how clients interact with applications through AWS Data Firehose, businesses can gain valuable insights into user behavior. This can drive content personalization strategies or optimize server architecture for better performance based on traffic patterns.</p> </li> <li> <p><strong>Automated Alerting Mechanism</strong>: Integrating AWS Data Firehose with alerting systems via this plugin allows teams to set up automated alerts based on specific metrics collected. For example, if a particular threshold is reached in the input data, alerts can trigger operations teams to investigate potential issues before they escalate.</p> </li> </ol>

Sumo Logic

<ol> <li> <p><strong>Real-Time System Monitoring Dashboard</strong>: Utilize the Sumo Logic plugin to continuously feed performance metrics from your servers into a Sumo Logic dashboard. This setup allows tech teams to visualize system health and load in real-time, enabling quicker identification of any performance bottlenecks or system failures through detailed graphs and metrics.</p> </li> <li> <p><strong>Automated Alerting System</strong>: Configure the plugin to send metrics that trigger alerts in Sumo Logic for specific thresholds such as CPU usage or memory consumption. By setting up automated alerts, teams can proactively address issues before they escalate into critical failures, significantly improving response times and overall system reliability.</p> </li> <li> <p><strong>Cross-System Metrics Aggregation</strong>: Integrate multiple Telegraf instances across different environments (development, testing, production) and funnel all metrics to a central Sumo Logic instance using this plugin. This aggregation enables comprehensive analysis across environments, facilitating better monitoring and informed decision-making across the software development lifecycle.</p> </li> <li> <p><strong>Custom Metrics with Dimensions Tracking</strong>: Use the Sumo Logic plugin to send customized metrics that include dimensions identifying various aspects of your infrastructure (e.g., environment, service type). This granular tracking allows for more tailored analytics, enabling your team to dissect performance across different application layers or business functions.</p> </li> </ol>

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