Alerts and automated retraining are essential components in the realm of machine learning and data science. Alerts serve as notifications that inform data scientists and engineers about significant changes in model performance or data quality, enabling timely interventions. Automated retraining, on the other hand, refers to the process of updating machine learning models based on new data or performance metrics without manual intervention. Together, these mechanisms ensure that models remain accurate and relevant over time, adapting to evolving data patterns and minimizing the risk of performance degradation. This synergy enhances the overall effectiveness of machine learning systems in production environments.