Outlier Detection is now a feature within the Grafana Machine Learning toolkit available on Grafana Cloud for Pro and Advanced users, designed to monitor groups of similar entities, such as Kubernetes pods, and alert users when anomalies occur. This tool is particularly useful for managing the complexity of horizontally scaled applications by comparing the behavior of similar pods to identify deviations, helping to address issues like higher error rates early. By using algorithms like DBSCAN and MAD, users can detect outliers by comparing current data with historical trends or identifying clusters, respectively. The feature integrates with Grafana Alerting to notify users of detected anomalies, and it allows for the adjustment of sensitivity settings to tailor outlier identification to specific needs. Grafana Cloud offers a free trial and ongoing support through its community channels, inviting users to explore data insights and make use of its comprehensive monitoring capabilities.