Control trace volume with OpenTelemetry tail-based sampling

OpenTelemetry tail-based sampling reduces observability costs and trace noise by buffering completed traces in the Collector and retaining those that contain errors, exceed latency thresholds, match debugging criteria, or meet other configured policies, unlike head-based sampling, which decides before a request finishes. Reliable tail sampling requires a gateway collector pattern that routes all spans with the same trace ID to one instance, while Span Metrics or RED metrics must be computed before sampling to preserve complete request, error, and latency visibility. Using a synthetic rideshare application, the guide demonstrates a layered policy approach that retains all error and slow traces, explicitly drops low-value successful health checks, reduces sampling for high-volume services, and applies probabilistic fallback sampling to ordinary traffic, reducing exported traces by about 98% while retaining accurate service-health metrics. It also addresses developer workflows through full sampling in development environments and force-sampling attributes, explains that explicit drop policies override sampling policies, and recommends monitoring collector metrics, sizing memory for buffered in-flight traces, tuning decision wait times and trace limits, and gradually refining policies to balance diagnostic value, system performance, and cost.

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