September 2026 Summaries

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Honeycomb is donating an adaptive tail sampling processor to the OpenTelemetry Collector, aiming to provide a more flexible alternative to traditional head, probabilistic, and static tail sampling approaches. Unlike conventional tail samplers, the processor buffers spans to evaluate full traces while making decisions soon after receiving a root span, helping reduce memory and CPU use. It combines configurable static rules, such as always retaining errors or dropping health checks, with trace fingerprinting that distinguishes traffic by attributes such as services, routes, response codes, and tenant identifiers. Adaptive rates are recalculated periodically to distribute either a percentage-based or throughput-based sampling budget across fingerprints, preserving visibility into low-volume requests while reducing data from high-volume paths and limiting costs during spikes or attacks. The processor also records sampling thresholds in OpenTelemetry trace state to support accurate backend extrapolation, and it is available ahead of upstream release through the Honeycomb OpenTelemetry Collector Distribution for deployments using OTLP, Kubernetes, or Docker.