The benefits of developing applications using microservices are clear, but it also introduces greater complexity in managing and troubleshooting distributed systems. To cut through this complexity, distributed tracing enables teams to track the path of each transaction as it travels through a distributed system, analyzing the interaction with every service it touches. This capability helps teams understand performance, visualize service dependencies, resolve performance issues quickly, measure overall system health, prioritize high-value areas for improvement, and gain insight into how to prevent reoccurrence. However, not all traces are equally actionable, and traditional head-based sampling methods may miss critical errors or unusual latency in high-throughput systems. Tail-based sampling provides a solution by observing and analyzing 100% of traces, allowing teams to visualize traces with errors or uncharacteristic slowness more quickly and pinpoint exactly where issues are. The flexibility to choose between different sampling methods based on the use case and cost/benefit analysis is essential in managing complex distributed systems.