OpenStack and AWS Timestream Integration

Input and output integration overview

<p>This plugin collects metrics from essential OpenStack services, facilitating the monitoring and management of cloud infrastructures.</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

OpenStack

<p>The OpenStack plugin allows users to collect performance metrics from various OpenStack services such as CINDER, GLANCE, HEAT, KEYSTONE, NEUTRON, and NOVA. It supports multiple OpenStack APIs to fetch critical metrics related to these services, enabling comprehensive monitoring and management of cloud resources. As organizations increasingly adopt OpenStack for their cloud infrastructure, this plugin plays a vital role in providing insights into resource usage, availability, and performance across the cloud environment. Configuration options allow for customized polling intervals and filtering unwanted tags to optimize performance and cardinals.</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

OpenStack

AWS Timestream

Input and output integration examples

OpenStack

<ol> <li> <p><strong>Cross-Cloud Management</strong>: Leverage the OpenStack plugin to monitor and manage multiple OpenStack clouds from a single Telegraf instance. By aggregating metrics across different clouds, organizations can gain insights into resource utilization and optimize their cloud architecture for cost and performance.</p> </li> <li> <p><strong>Automated Scaling Based on Metrics</strong>: Integrate the metrics gathered from OpenStack into an automated scaling solution. For example, if the plugin detects that a specific service’s performance is degraded, it can trigger auto-scaling rules to launch additional instances, ensuring that system performance remains optimal under varying workloads.</p> </li> <li> <p><strong>Performance Monitoring Dashboard</strong>: Use data collected by the OpenStack Telegraf plugin to power real-time monitoring dashboards. This setup provides visualizations of key metrics from OpenStack services, enabling stakeholders to quickly identify trends, pinpoint issues, and make data-driven decisions in managing their cloud infrastructure.</p> </li> <li> <p><strong>Reporting and Analysis of Service Availability</strong>: By utilizing the metrics collected from various OpenStack services, teams can generate detailed reports on service availability and performance over time. This information can help identify recurring issues, improve service delivery, and make informed decisions regarding changes in infrastructure or service configuration.</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.