John Pruitt

Of the three observability data types supported by OpenTelemetry (metrics, logs, and traces) the latter is the one with most potential. Tracing gives users insights into how requests are processed by microservices in a modern, cloud-native architecture.

Jaeger and Grafana can visualize a single trace, showing how an individual request traversed your entire system. This helps for distributed debugging and analysis, but using traces only this way is limiting.

What if you stored tracing data in a SQL database? You could ask global questions about your system. You could find slow communication paths, where the error rate spiked since the last deployment, or where the request rate suddenly dropped. Thus, tracing can be used proactively to help you spot issues before your customers do.

This talk will show you how to do all the above by ingesting OpenTelemetry traces into a PostgreSQL/TimescaleDB database, and building custom dashboards using SQL to make the most out of your tracing data.

• What is a trace?
• What is OpenTelemetry?
• View an OpenTelemetry trace in Jaeger
• Overview of OpenTelemetry trace data model
• How it might be represented in a relational-database model - PostgreSQL
• Demonstrate a variety of SQL queries which provide insights into a system explaining the value
• View these queries in a Grafana dashboard