2025-10-30 –, Auditorium
Debugging microservices should not feel like detective work. When logs cannot tell the full story, it is time to embrace modern observability.
This session shows you how to collect metrics, logs, and traces from your Python applications using OpenTelemetry’s auto-instrumentation, then visualize everything in Grafana to quickly pinpoint performance issues and errors.
You will leave with practical skills to implement production-grade observability using open-source tools and open standards, with minimal code changes required.
As software systems grow in complexity, traditional logging is no longer enough. Without proper observability, diagnosing errors or performance issues easily becomes guesswork. Fortunately, open-source technologies like OpenTelemetry and Grafana have made powerful observability more accessible than ever, offering end-to-end visibility into your systems with minimal friction.
In this session, you will learn how to:
- Get started quickly with OpenTelemetry’s Python auto-instrumentation to collect metrics, logs, and traces from your applications
- Visualize telemetry data in Grafana using dashboards and views for real-time insights and root-cause analysis
- Level up observability by customizing instrumentation, correlating between signals, and propagating context across services
Through practical code examples and demos, you will walk away with a clear, hands-on understanding of how to build production-grade observability into your Python applications by leveraging open-source software and open standards: fast, flexible, and future-proof.
Johanna Öjeling is a Senior Software Engineer at Grafana Labs and an OpenTelemetry member with experience spanning backend, data, and platform engineering. She specializes in distributed, data-intensive systems and is committed to developer experience and open source.