AWS Glue Data Quality makes ETL anomaly detection free and improves anomaly predictions

AWS Glue Data Quality now offers improved anomaly detection with a new observation mode that reduces detection of false anomalies and removes pricing for anomaly detection in ETL jobs. Customers using notebook-based or exploratory workflows now benefit from smarter anomaly detection that gracefully handles irregular data arrival intervals. This new capability avoids over-extrapolating trends by using a constant baseline instead of a linear trend, delivering more accurate alerts and reducing noise so teams can focus on genuine anomalies.

The new anomaly detection observation mode is particularly useful for exploratory data analysis, datasets with flat or random patterns, workloads without predictable trends and cases where you run data quality checks on varying schedules or in interactive environments like notebooks. Additionally, anomaly detection for AWS Glue ETL jobs is now available at no additional cost, so you can monitor data quality anomalies across all your Glue pipelines without worrying about pricing.

These improvements are available in all AWS commercial regions and AWS GovCloud (US) regions.

To get started, visit the AWS Glue Data Quality documentation. To learn more about pricing, see the AWS Glue pricing page.