Monitor Ray applications and clusters with Datadog

This article details how a team at Grafana Labs improved their ability to detect faulty software deployments. Initially relying on manual review of unlabeled data, they transitioned to a supervised learning approach by creating a labeled dataset from anomaly detection alerts and incident reports. This allowed them to build a model predicting deployment success/failure, ultimately leading to faster and more accurate identification of problematic deployments.