Distributed tracing in Kubernetes apps: What you need to know

Distributed tracing is an essential tool for monitoring Kubernetes applications, providing insights into application health and performance by tracking interactions between microservices. Based on Google's Dapper paper, it uses spans—unique units of work with identifiers—to reconstruct transactions and understand service interactions, offering a more comprehensive view than traditional logging. Distributed tracing is crucial for Kubernetes observability, allowing developers to identify service dependencies, detect anomalies, and enhance debugging through end-to-end visibility. Tools like Grafana Tempo, supporting protocols such as OpenTelemetry, Zipkin, and Jaeger, facilitate distributed tracing by collecting and storing telemetry data efficiently, offering scalable and cost-effective solutions for tracing in complex cloud environments. OpenTelemetry, the convergence of OpenTracing and OpenCensus, is emerging as a standard, backed by major IT vendors, and offers robust instrumentation support across multiple programming languages, enhancing the capability of distributed tracing tools like Grafana Tempo to integrate seamlessly without modifying application code.