Amazon Timestream for LiveAnalytics is a scalable serverless time series database designed to handle trillions of data points daily. It offers auto-scaling, data lifecycle management, and high availability. Prometheus, used for systems monitoring, stores metrics as time series data and collects data through a pull model. By integrating Prometheus with Timestream, users can benefit from serverless scalability, correlation, SQL-based querying, enhanced data exploration, and cost-effectiveness.
The Timestream for LiveAnalytics Prometheus Connector serves as a bridge between Prometheus and Timestream, allowing Prometheus to use Timestream for remote storage. By leveraging a one-click deployment option, users can deploy the connector as a Lambda function through an AWS CloudFormation template. The connector can be run locally, as a Docker container, or as an AWS Lambda function.
To configure Prometheus to use Timestream for remote storage, users need to update the prometheus.yml configuration file with the appropriate URLs obtained from the deployment. Once configured, Prometheus will start writing data to Timestream. Users can verify the functionality through Prometheus’ expression browser and by running sample queries in Timestream. To clean up resources and avoid unnecessary costs, users should delete databases, tables, and the CloudFormation stack once the setup is no longer needed.
The Timestream for LiveAnalytics Prometheus Connector enhances the capabilities of Prometheus by leveraging Timestream’s serverless architecture and advanced analytics features. This integration provides users with a powerful tool for analyzing monitoring data and making informed decisions. The collaboration between Improving and AWS in developing this solution demonstrates a commitment to delivering innovative solutions for handling time series data efficiently.
Article Source
https://aws.amazon.com/blogs/database/introducing-the-amazon-timestream-for-liveanalytics-prometheus-connector/