Distributed Tracing<\/a> is a diagnostic technique used to monitor and profile applications, specifically those built using a Microservices<\/a> architecture. By tracking the path of a request as it moves through various services, it provides developers with visibility into complex system behaviors and performance bottlenecks. This process is a core pillar of modern Observability<\/a>.<\/p> The primary unit of data in this system is the Span<\/a>, which represents a single logical unit of work. Each span includes a name, start time, duration, and metadata. When multiple spans are combined, they form a Trace<\/a>, representing the end-to-end journey of a request. To maintain the continuity of a trace across network boundaries, Context Propagation<\/a> is employed to pass unique identifiers through HTTP headers or message metadata. The W3C Trace Context<\/a> specification has become the industry standard for ensuring interoperability between different tracing tools.<\/p> Several open-source projects have shaped the landscape of tracing. Dapper<\/a>, a project by Google, laid the conceptual groundwork. Today, Jaeger<\/a> and Zipkin<\/a> are widely used for collecting and visualizing trace data. Most modern implementations now leverage OpenTelemetry<\/a>, an CNCF<\/a> project that provides a unified set of APIs and SDKs. As noted in the OpenTelemetry Documentation<\/a> and Jaeger Architecture Guide<\/a>, distributed tracing is indispensable for root cause analysis in Cloud-Native<\/a> environments.<\/p>