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fix typos and adjust overview
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deploy-manage/autoscaling.md

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The autoscaling feature enables an operator to configure tiers of nodes that self-monitor whether or not they need to scale based on an operator-defined policy. Then, via the autoscaling API, an Elasticsearch cluster can report whether or not it needs additional resources to meet the policy. For example, an operator could define a policy that a warm tier should scale on available disk space. Elasticsearch would monitor and forecast the available disk space in the warm tier, and if the forecast is such that the cluster will soon not be able to allocate existing and future shard copies due to disk space, then the autoscaling API would report that the cluster needs to scale due to disk space. It remains the responsibility of the operator to add the additional resources that the cluster signals it requires.
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The autoscaling feature allows an operator to create tiers of nodes. These nodes monitor themselves to decide if they need to scale, based on an operator-defined policy. An Elasticsearch cluster can use the autoscaling API to report if it needs more resources to meet the policy. For example, an operator could define a policy that a warm tier should scale on available disk space. Elasticsearch monitors disk space in the warm tier. If it predicts low disk space for current and future shard copies, the autoscaling API will report that the cluster needs to scale. It remains the responsibility of the operator to add the additional resources that the cluster signals it requires.
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A policy is composed of a list of roles and a list of deciders. Nodes matching the roles are governed by the policy. The deciders provide independent estimates of the capacity required. See [Autoscaling deciders](../deploy-manage/autoscaling/autoscaling-deciders.md) for more information on the deciders available.
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A policy is composed of a list of roles and a list of deciders. The policy governs the nodes matching the roles. The deciders provide independent estimates of the capacity required. See [Autoscaling deciders](../deploy-manage/autoscaling/autoscaling-deciders.md) for details on available deciders.
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Autoscaling supports the scale-up and scale-down of dedicated {{ml}} nodes. Autoscaling also supports the scale-up of data nodes based on storage.
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Autoscaling supports:
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* Scaling machine learning nodes up and down.
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* Scaling data nodes up based on storage.
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Autoscaling is not supported on Debian 8.
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Autoscaling helps you to more easily manage your deployments by adjusting their available resources automatically, and currently supports scaling for both data and machine learning nodes, or machine learning nodes only. Check the following sections to learn more:
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To learn more about configuring and managing autoscaling, check the following sections:
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* [Overview](#ec-autoscaling-intro)
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* [When does autoscaling occur?](#ec-autoscaling-factors)

deploy-manage/autoscaling/ec-hosted-autoscaling-api-example.md

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$$$ec-autoscaling-api-example-requirements-table$$$
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* ✓ = Include the property.
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+ = Include the property.
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* = Do not include the property.
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* These rules match the behavior of the {{ecloud}} Console.
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+ These rules match the behavior of the {{ecloud}} Console.
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+ * The `elasticsearch` object must contain the property `"autoscaling_enabled": true`.
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* `*` The `elasticsearch` object must contain the property `"autoscaling_enabled": true`.
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## API request example [ec_api_request_example]

deploy-manage/autoscaling/ece-autoscaling-api-example.md

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* ✓ = Include the property.
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* These rules match the behavior of the Elastic Cloud Enterprise user console.
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+ These rules match the behavior of the Elastic Cloud Enterprise user console.
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+ * The `elasticsearch` object must contain the property `"autoscaling_enabled": true`.
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* `*` The `elasticsearch` object must contain the property `"autoscaling_enabled": true`.
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## API request example [ece_api_request_example]

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