Elastic Stack's machine learning capabilities have been enhanced in version 6.4 to better handle changes in system behavior, particularly in identifying anomalies in time series data. The improvements focus on addressing concept drift, where historical data models may become inaccurate over time due to recurring, gradual, or sudden changes in the data. The updated system introduces parametric forms for detecting sudden changes, allowing for more efficient and robust model adaptation. This approach enables the model to seamlessly balance between adapting quickly to new data while maintaining stability and accuracy in predictions, particularly when sudden shifts occur, such as linear scaling or step changes. The enhancements allow for better anomaly detection by using a combination of historical data and real-time updates, making the model more resilient to unusual data intervals. Users can explore these advancements by trying out Elastic Stack's features with a 30-day trial or on Elastic Cloud.