Keep the data flowing with Model-driven Operations
In this video we examine Model-driven Operations and apply it to DataOps to understand how teams can deliver more, spend more time in flow state, and just have more fun.
In this tutorial, we will go through a working example of a Python application auto-instrumented with OpenTelemetry. To keep things simple, we will create a basic “Hello World” application using Flask, instrument it with OpenTelemetry’s Python client library to generate trace data and send it to an OpenTelemetry Collector. The Collector will then export the trace data to an external distributed tracing analytics tool of our choice.