Sampling in Distributed Tracing
Sampling is still one of the biggest challenges in distributed tracing. While the basic concept is easy to grasp, the number of choices and their trade-offs requires learning about the techniques and your own workload. In this session, we are giving you all the knowledge required to master the sampling techniques: we’ll talk about head and tail-based sampling, as well as adaptive sampling, and we’ll wrap it up with a bonus discussion on trace aggregation. You’ll leave this session ready to implement scenarios, from the simple “probabilistic head-sampling” up to the complex “scalable tail-based sampling” using open source tools like OpenTelemetry Collector.
More about Juraci Paixão Kröhling
Juraci Paixão Kröhling is a software engineer at Red Hat working in the Distributed Tracing team. He’s a maintainer on the Jaeger project and contributor to the OpenTelemetry project. He has talked about distributed tracing at conferences like KubeCon, OpenSource Summit, FOSDEM, Devoxx, JavaLand, GIDS, among others.