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solutions/observability/apps/transaction-sampling.md

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@@ -139,7 +139,7 @@ Tail-based sampling, by definition, requires storing events locally temporarily,
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In APM Server implementation, the events are stored temporarily on disk instead of memory for better scalability. Therefore, it requires local disk storage proportional to APM event ingestion rate, and additional memory to facilitate disk reads and writes. Insufficient [storage limit](../../../solutions/observability/apps/transaction-sampling.md#sampling-tail-storage_limit) causes sampling to be bypassed.
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It is recommended to use fast disks, for example, NVMe SSDs, when enabling tail-based sampling, as disk throughput and IO may be the performance bottleneck to tail-based sampling, and APM event ingestion as a whole. Disk writes are proportional to event ingest rate, and disk reads are proportional to event ingest rate and sampling rate.
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It is recommended to use fast disks, such as NVMe SSDs, when enabling tail-based sampling. Disk throughput and I/O may become performance bottlenecks for tail-based sampling and APM event ingestion overall. Disk writes are proportional to the event ingest rate, while disk reads are proportional to both the event ingest rate and the sampling rate.
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To demonstrate the performance overhead and requirements, here are some numbers from a standalone APM Server 9.0 deployed on AWS EC2, under full load receiving APM events containing only traces, assuming no backpressure from Elasticsearch, and 10% sample rate in tail sampling policy. They are for reference only, and may vary depending on factors like sampling rate, average event size, and average number of events per distributed trace.
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