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• OpenSearch Anomaly Detection
• Documentation
• Contributing
• Code of Conduct
• Security
• License
• Copyright

The OpenSearch Anomaly Detection plugin enables you to leverage Machine Learning based algorithms to automatically detect anomalies as your log data is ingested. Combined with OpenSearch Alerting, you can monitor your data in near real time and automatically send alert notifications . With an intuitive OpenSearch Dashboards interface, and a powerful API, it is easy to set up, tune, and monitor your anomaly detectors.

Anomaly detection is using the Random Cut Forest (RCF) algorithm for detecting anomalous data points.

Anomaly detections run a scheduled job using job-scheduler.

You can use this plugin with the same version of the OpenSearch Alerting Plugin to create monitors based on created anomaly detectors. A scheduled monitor run checks the anomaly detection results regularly, and collects anomalies to trigger alerts based on custom trigger conditions.

Please see our documentation.

See developer guide and how to contribute to this project.

This project has adopted the Amazon Open Source Code of Conduct. For more information see the Code of Conduct FAQ, or contact [email protected] with any additional questions or comments.

If you discover a potential security issue in this project we ask that you notify AWS/Amazon Security via our vulnerability reporting page. Please do not create a public GitHub issue.

This project is licensed under the Apache v2.0 License.

Copyright OpenSearch Contributors. See NOTICE for details.