Grafana Machine Learning has introduced a new feature that enhances its forecasting capabilities by accounting for holidays, addressing the limitations of its existing model, Prophet, which already considers yearly, weekly, and daily seasonality in time series data. This feature allows users to incorporate specific predictable shifts in data by informing the model of past and future holiday occurrences, either by directly adding them in the UI or by providing a public iCalendar address. The functionality proves particularly useful for adjusting forecasts during holidays, as demonstrated with U.S. public holidays, where standard models might misinterpret traffic patterns as regular weekdays. By linking holidays to forecasts, Grafana Machine Learning can more accurately predict behaviors during these periods, thus improving alert accuracy and reducing false positives. This advancement is part of Grafana Cloud Pro and Advanced plans, offering customers the ability to refine their time series forecasts by integrating real-world events into their data analysis.