Distributed tracing is a crucial element in enhancing application performance by tracking individual requests as they traverse through various services within an infrastructure, providing insights that metrics and logs alone cannot offer. While metrics are efficient for aggregating data and logs help in understanding sequential events, they both lack the ability to pinpoint the exact behavior of a single request within a service. Grafana Labs addresses this gap with Grafana Tempo, a scalable and cost-effective distributed tracing backend that simplifies the tracing process by relying solely on object storage, eliminating the need for complex clusters like Elasticsearch or Cassandra. Tempo integrates seamlessly with other Grafana tools, such as logs and Prometheus exemplars, to provide a comprehensive overview of application performance. Distributed tracing, effective in both microservices and monolithic architectures, enables the diagnosis of performance issues by revealing the detailed path and duration of requests, thereby guiding developers on where to focus their optimization efforts. Context propagation plays a vital role in tracing by passing trace information across services, ensuring that the backend can reconstruct the entire trace for analysis. This guide highlights the benefits of incorporating distributed tracing and encourages developers to integrate it into their observability practices for improved application performance.