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With the increasing complexity that comes with adopting distributed architectures like Kafka, it is difficult to identify and triage performance anomalies. Implementing Distributed Tracing technologies like OpenTelemetry can add context to the messages flowing through your system, allowing us to visualize the data flow to pinpoint bottlenecks, bugs, and other performance issues. However, implementing end-to-end distributed tracing can be challenging for multi-request and asynchronous processes built on Kafka.
This talk will walk through how to use OpenTelemetry to tell the full story of a request as it travels through your Kafka producer, queue, and consumer. First, we will learn how context propagation works in OpenTelemetry with W3C and B3 protocols. Then, we will go through the problems faced when instrumenting asynchronous requests. Finally, we will go through the context propagation implementation of the OpenTelemetry Kafka exporter, tracing multi-request and asynchronous processes.