Predictive Analytics with Time-series Machine Learning on Amazon Timestream

This blog post explains how to perform predictive analytics on time-series DevOps data (CPU, memory, transactions per second) stored in Amazon Timestream using Amazon SageMaker's built-in DeepAR forecasting algorithm. This enables proactive capacity planning to prevent potential business interruptions.

Specifically, the article covers:

• Overview of the solution architecture using Timestream and SageMaker
• Prerequisites and launching a hands-on lab with a CloudFormation template
• Preparing time-series data from Timestream for analysis
• Training a machine learning model using the DeepAR algorithm
• Generating predictive insights and visualizing the results
• Best practices for data aggregation in Timestream
• Cleanup steps to avoid incurring charges
• Conclusion and additional resources