Databases are the backbone of every application, yet monitoring them effectively remains a challenge. In this session, we walk through monitoring production databases powering an e-commerce platform Valkey for caching and PostgreSQL for the catalog deployed on Kubernetes & Docker, using OpenSearch and Prometheus as the observability backbone.

We demonstrate a complete OpenTelemetry-based pipeline: instrumenting both databases with OTel SDKs, routing telemetry through Data Prepper to store time-series metrics in Prometheus and traces/logs in OpenSearch. With AI-assisted investigation using text-to-PPL and text-to-PromQL, engineers query live telemetry in natural language asking "show me slow queries in the catalog service in the last hour" without writing complex syntax.

We also show how to use AI to generate RCA visualizations and surface performance insights across your database fleet. Whether you manage a handful of databases or hundreds, you'll leave with practical patterns for building an OpenTelemetry-native database observability stack.