⭐️OpenTelemetryの仕様: Scaling collectors with the tail sampling processor

https://github.com/open-telemetry/opentelemetry-collector-contrib/blob/6dfefe3e54558157bbd8093b7fbc53c52350965a/processor/tailsamplingprocessor/README.md?plain=1#L17

The tail sampling processor samples traces based on a set of defined policies. All spans for a given trace MUST be received by the same collector instance for effective sampling decisions.

https://github.com/open-telemetry/opentelemetry-collector-contrib/blob/6dfefe3e54558157bbd8093b7fbc53c52350965a/processor/tailsamplingprocessor/README.md?plain=1#L560

This processor requires all spans for a given trace to be sent to the same collector instance for the correct sampling decision to be derived. When scaling the collector, you’ll then need to ensure that all spans for the same trace are reaching the same collector. You can achieve this by having two layers of collectors in your infrastructure: one with the [load balancing exporter][loadbalancing_exporter], and one with the tail sampling processor.

tail-based samplingはトレース全体を1箇所で評価する必要があるため、Collectorをスケールアウトする場合は loadbalancingexporter を使った2層構成にして、「同じTrace IDのデータが必ず同じCollectorに集まる仕組み」にする必要がある。

=> これ、span欠損の要因になりそう… => 以下に同一トレースのspanを同じCollectorで処理させるか（tail-based samplingをしている場合は）