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[Docs] Remove tech preview notice from downsampling docs (#92913)
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docs/reference/data-streams/downsampling-ilm.asciidoc

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<titleabbrev>Run downsampling with ILM</titleabbrev>
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This is a simplified example that allows you to see quickly how
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<<downsampling,downsampling>> works as part of an ILM policy to reduce the
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storage size of a sampled set of metrics. The example uses typical Kubernetes

docs/reference/data-streams/downsampling-manual.asciidoc

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<titleabbrev>Run downsampling manually</titleabbrev>
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This is a simplified example that allows you to see quickly how
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<<downsampling,downsampling>> works to reduce the storage size of a time series
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index. The example uses typical Kubernetes cluster monitoring data. To test out

docs/reference/data-streams/downsampling.asciidoc

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[[downsampling]]
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=== Downsampling a time series data stream
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Downsampling provides a method to reduce the footprint of your <<tsds,time
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series data>> by storing it at reduced granularity.
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docs/reference/data-streams/tsds.asciidoc

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A time series data stream (TSDS) models timestamped metrics data as one or
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more time series.
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You can use a TSDS to store metrics data more efficiently. In our benchmarks,
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metrics data stored in a TSDS used 44% less disk space than a regular data
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stream.

docs/reference/ilm/actions/ilm-downsample.asciidoc

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[[ilm-downsample]]
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=== Downsample
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Phases allowed: hot, warm, cold.
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Aggregates a time series (TSDS) index and stores

docs/reference/indices/downsample-data-stream.asciidoc

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<titleabbrev>Downsample</titleabbrev>
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Aggregates a time series (TSDS) index and stores
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pre-computed statistical summaries (`min`, `max`, `sum`, `value_count` and
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`avg`) for each metric field grouped by a configured time interval. For example,

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