Tools like Etsy's Kale are gaining in popularity with site reliability engineers and eng. groups doing continuous deployment. Kale allows us to monitor millions of metrics for anomalies as well as finding correlations between anomalies. Kale's anomaly detection is based on an ensemble of statistical techniques like median absolute deviation, grubbs, 3-sigma, etc. The focus of this talk is to see if ML algorithms can do better.