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Clarify docs around disk capacity expectation.
Make it explicit that es expects disks to have the same capacity across all the nodes in the same dat tier.
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docs/reference/datatiers.asciidoc

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[[data-tiers]]
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== Data tiers
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A _data tier_ is a collection of <<modules-node,nodes>> within a cluster that share the same
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<<node-roles,data node role>>, and a hardware profile that's appropriately sized for the role. Elastic recommends that nodes in the same tier share the same
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hardware profile to avoid <<hotspotting,hot spotting>>.
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A _data tier_ is a collection of <<modules-node,nodes>> within a cluster that share the same
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<<node-roles,data node role>>, and a hardware profile that's appropriately sized for the role. Elastic recommends that nodes in the same tier share the same
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hardware profile to avoid <<hotspotting,hot spotting>>.
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The data tiers that you use, and the way that you use them, depends on the data's <<data-management,category>>.
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The following data tiers are can be used with each data category:
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Content data:
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* <<content-tier,Content tier>> nodes handle the indexing and query load for non-timeseries
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* <<content-tier,Content tier>> nodes handle the indexing and query load for non-timeseries
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indices, such as a product catalog.
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Time series data:
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* <<hot-tier,Hot tier>> nodes handle the indexing load for time series data,
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* <<hot-tier,Hot tier>> nodes handle the indexing load for time series data,
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such as logs or metrics. They hold your most recent, most-frequently-accessed data.
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* <<warm-tier,Warm tier>> nodes hold time series data that is accessed less-frequently
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and rarely needs to be updated.
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<<ilm-searchable-snapshot,{search-snaps}>> on the cold tier. These fully mounted
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indices eliminate the need for replicas, reducing required disk space by
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approximately 50% compared to the regular indices.
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* <<frozen-tier,Frozen tier>> nodes hold time series data that is accessed
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* <<frozen-tier,Frozen tier>> nodes hold time series data that is accessed
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rarely and never updated. The frozen tier stores <<partially-mounted,partially
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mounted indices>> of <<ilm-searchable-snapshot,{search-snaps}>> exclusively.
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This extends the storage capacity even further — by up to 20 times compared to
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the warm tier.
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the warm tier.
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TIP: The performance of an {es} node is often limited by the performance of the underlying storage and hardware profile.
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For example hardware profiles, refer to Elastic Cloud's {cloud}/ec-reference-hardware.html[instance configurations].
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TIP: The performance of an {es} node is often limited by the performance of the underlying storage and hardware profile.
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For example hardware profiles, refer to Elastic Cloud's {cloud}/ec-reference-hardware.html[instance configurations].
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Review our recommendations for optimizing your storage for <<indexing-use-faster-hardware,indexing>> and <<search-use-faster-hardware,search>>.
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IMPORTANT: {es} generally expects nodes within a data tier to share the same
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hardware profile. Variations not following this recommendation should be
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IMPORTANT: {es} generally expects nodes within a data tier to share the same hardware profile
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and have the same disk capacity. Variations not following this recommendation should be
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carefully architected to avoid <<hotspotting,hot spotting>>.
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The way data tiers are used often depends on the data's category:
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- Content data remains on the <<content-tier,content tier>> for its entire
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data lifecycle.
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data lifecycle.
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- Time series data may progress through the
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descending temperature data tiers (hot, warm, cold, and frozen) according to your
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performance, resiliency, and data retention requirements.
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You can automate these lifecycle transitions using the <<data-streams,data stream lifecycle>>, or custom <<index-lifecycle-management,{ilm}>>.
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- Time series data may progress through the
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descending temperature data tiers (hot, warm, cold, and frozen) according to your
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performance, resiliency, and data retention requirements.
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You can automate these lifecycle transitions using the <<data-streams,data stream lifecycle>>, or custom <<index-lifecycle-management,{ilm}>>.
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[discrete]
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[[available-tier]]
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as time series data such as logs and metrics. From a resiliency perspective the indices in this
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tier should be configured to use one or more replicas.
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The content tier is required and is often deployed within the same node
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The content tier is required and is often deployed within the same node
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grouping as the hot tier. System indices and other indices that aren't part
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of a data stream are automatically allocated to the content tier.
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of a data stream are automatically allocated to the content tier.
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// end::content-tier[]
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[discrete]
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by default {es} sets the `_tier_preference`
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to `data_hot` to automatically allocate the index shards to the hot tier.
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At the time of index creation, you can override the default setting by explicitly setting
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At the time of index creation, you can override the default setting by explicitly setting
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the preferred value in one of two ways:
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- Using an <<index-templates,index template>>. Refer to <<getting-started-index-lifecycle-management,Automate rollover with ILM>> for details.
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- Within the <<indices-create-index,create index>> request body.
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- Within the <<indices-create-index,create index>> request body.
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You can override this
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setting after index creation by <<indices-update-settings,updating the index setting>> to the preferred
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value.
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You can override this
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setting after index creation by <<indices-update-settings,updating the index setting>> to the preferred
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value.
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This setting also accepts multiple tiers in order of preference. This prevents indices from remaining unallocated if no nodes are available in the preferred tier. For example, when {ilm} migrates an index to the cold phase, it sets the index `_tier_preference` to `data_cold,data_warm,data_hot`.
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To remove the data tier preference
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setting, set the `_tier_preference` value to `null`. This allows the index to allocate to any data node within the cluster. Setting the `_tier_preference` to `null` does not restore the default value. Note that, in the case of managed indices, a <<ilm-migrate,migrate>> action might apply a new value in its place.
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To remove the data tier preference
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setting, set the `_tier_preference` value to `null`. This allows the index to allocate to any data node within the cluster. Setting the `_tier_preference` to `null` does not restore the default value. Note that, in the case of managed indices, a <<ilm-migrate,migrate>> action might apply a new value in its place.
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[discrete]
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[[data-tier-allocation-value]]
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==== Determine the current data tier preference
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You can check an existing index's data tier preference by <<indices-get-settings,polling its
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You can check an existing index's data tier preference by <<indices-get-settings,polling its
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settings>> for `index.routing.allocation.include._tier_preference`:
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[source,console]
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[[data-tier-allocation-troubleshooting]]
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==== Troubleshooting
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The `_tier_preference` setting might conflict with other allocation settings. This conflict might prevent the shard from allocating. A conflict might occur when a cluster has not yet been completely <<troubleshoot-migrate-to-tiers,migrated
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to data tiers>>.
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The `_tier_preference` setting might conflict with other allocation settings. This conflict might prevent the shard from allocating. A conflict might occur when a cluster has not yet been completely <<troubleshoot-migrate-to-tiers,migrated
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to data tiers>>.
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This setting will not unallocate a currently allocated shard, but might prevent it from migrating from its current location to its designated data tier. To troubleshoot, call the <<cluster-allocation-explain,cluster allocation explain API>> and specify the suspected problematic shard.
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