OpenTelemetry and AWS Timestream Integration

Input and output integration overview

<p>This plugin receives traces, metrics, and logs from OpenTelemetry clients and agents via gRPC, enabling comprehensive observability of applications.</p>

<p>The AWS Timestream Telegraf plugin enables users to send metrics directly to Amazon’s Timestream service, which is designed for time series data management. This plugin offers a variety of configuration options for authentication, data organization, and retention settings.</p> <p>With the coming End of Life of AWS Timestream for LiveAnalytics, you can easily switch to AWS Timestream for InfluxDB or other verions of InfluxDB hosted on AWS by using the <a href="https://www.influxdata.com/integrations/influxdb/">InfluxDB Telegraf plugin</a>. Learn more about <a href="https://www.influxdata.com/influxdb-cloud-on-aws/">AWS and InfluxDB</a></p>

Integration details

OpenTelemetry

<p>The OpenTelemetry plugin is designed to receive telemetry data such as traces, metrics, and logs from clients and agents implementing OpenTelemetry via gRPC. This plugin initiates a gRPC service that listens for incoming telemetry data, making it distinct from standard plugins that collect metrics at defined intervals. The OpenTelemetry ecosystem aids developers in observing and understanding their applications’ performance by providing a vendor-neutral way to instrument, generate, collect, and export telemetry data. Key features of this plugin include customizable connection timeouts, adjustable maximum message sizes for incoming data, and options for specifying span, log, and profile dimensions to tag the incoming metrics. With this flexibility, organizations can tailor their telemetry collection to meet precise observability requirements and ensure seamless data integration into systems like InfluxDB.</p>

AWS Timestream

<p>This plugin is designed to efficiently write metrics to Amazon’s Timestream for LiveAnalytics service. With AWS no longer accepting new users for their LiveAnalytics service, consider using the <a href="https://www.influxdata.com/integrations/influxdb/">InfluxDB plugin</a> with AWS Timestream for InfluxDB or other <a href="https://www.influxdata.com/influxdb-cloud-on-aws/">InfluxDB options available on AWS</a>. This plugin Telegraf can send data collected from various sources and supports a flexible configuration for authentication, data organization, and retention management. It utilizes a credential chain for authentication, allowing various methods such as web identity, assumed roles, and shared profiles. Users can define how metrics are organized in Timestream—whether to use a single table or multiple tables, alongside control over aspect such as retention periods for both magnetic and memory stores. A key feature is its ability to handle multi-measure records, enabling efficient data ingestion and helping to reduce the overhead of multiple writes. In terms of error handling, the plugin includes mechanisms for addressing common issues related to AWS errors during data writes, such as retry logic for throttling and the ability to create tables as needed.</p>

Configuration

OpenTelemetry

AWS Timestream

Input and output integration examples

OpenTelemetry

<ol> <li> <p><strong>Unified Monitoring Across Services</strong>: Use the OpenTelemetry plugin to collect and consolidate telemetry data from various microservices within a Kubernetes environment. By instrumenting each service with OpenTelemetry, you can utilize this plugin to gather a holistic view of application performance and dependencies in real-time, enabling faster troubleshooting and improved reliability of complex systems.</p> </li> <li> <p><strong>Enhanced Debugging with Traces</strong>: Implement this plugin to capture end-to-end traces of requests flowing through multiple services. For instance, when a user initiates a transaction that triggers several backend services, the OpenTelemetry plugin can record detailed traces that highlight performance bottlenecks, giving developers the necessary insights to debug issues and optimize their code.</p> </li> <li> <p><strong>Dynamic Load Testing and Performance Monitoring</strong>: Leverage the capabilities of this plugin during load testing phases by collecting live metrics and traces under simulated higher loads. This approach helps to evaluate the resilience of the application components and identify potential performance degradations preemptively, ensuring a smooth user experience in production.</p> </li> <li> <p><strong>Integrated Logging and Metrics for Real-Time Monitoring</strong>: Combine the OpenTelemetry plugin with logging frameworks to gather real-time logs alongside metric data, creating a powerful observability platform. For example, integrate it within a CI/CD pipeline to monitor builds and deployments, while collecting logs that help diagnose failures or performance issues in real-time.</p> </li> </ol>

AWS Timestream

<ol> <li> <p><strong>IoT Data Metrics</strong>: Use the Timestream plugin to send real-time metrics from IoT devices to Timestream, allowing for quick analysis and visualization of sensor data. By organizing device readings into a time series format, users can track trends, identify anomalies, and streamline operational decisions based on device performance.</p> </li> <li> <p><strong>Application Performance Monitoring</strong>: Leverage Timestream alongside application monitoring tools to send metrics about service performance over time. This integration enables engineers to perform historical analysis of application performance, correlate it with business metrics, and optimize resource allocation based on usage patterns viewed over time.</p> </li> <li> <p><strong>Automated Data Archiving</strong>: Configure the Timestream plugin to write data to Timestream while simultaneously managing retention periods. This setup can automate archiving strategies, ensuring that older data is preserved according to predefined criteria. This is especially useful for compliance and historical analysis, allowing businesses to maintain their data lifecycle with minimal manual intervention.</p> </li> <li> <p><strong>Multi-Application Metrics Aggregation</strong>: Utilize the Timestream plugin to aggregate metrics from multiple applications into Timestream. By creating a unified database of performance metrics, organizations can gain holistic insights across various services, improving visibility into system-wide performance and facilitating cross-application troubleshooting.</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.