At Elastic{ON} 2018, machine learning developments for the Elastic Stack were showcased, highlighting its evolution from automated anomaly detection to event forecasting using Elasticsearch time series data. Steve Dodson, the team lead for machine learning at Elastic, demonstrated new features using New York City taxi data, identifying anomalies such as low trip volumes during a snowstorm and forecasting future taxi trip times. The forecasting capabilities, which aggregate historical data to predict future trends, were a focal point, offering potential for operational optimizations such as disk space management and KPI trend analysis. These advancements, demonstrated through various sessions, illustrate how Elastic's machine learning tools can automate and enhance operations across different use cases, with further insights provided into the modeling techniques behind these capabilities.