Applications using distributed architecture are becoming more frequent and complex through Kubernetes deployments. Developers are more concerned about generating useful logs, gathering metrics, and thus maintaining the application with precise data about the performance baseline.

Therefore, to help developers enhance this instrumenting approach, the OpenTelemetry project leverages analytical capabilities by expanding the possibilities to collect and export telemetry data from the Kubernetes workload.

In this talk, I will share an easy way for the audience to achieve the auto-instrumenting of different programming languages' workloads using the OpenTelemetry Operator.