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[DOCS] Separates ES and Kibana security info on ML setup page (elastic#1649)
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docs/en/stack/ml/setup.asciidoc

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<titleabbrev>Setup and security</titleabbrev>
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To use the {stack} {ml-features}, you must have the
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{subscriptions}[appropriate subscription] and at least one
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To use the {stack} {ml-features}, you must have the
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{subscriptions}[appropriate subscription] and at least one
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<<ml-nodes,{ml} node>> in your cluster.
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In {kib}, the {ml-features} must be visible in your
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{kibana-ref}/xpack-spaces.html#spaces-control-feature-visibility[space] and your
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source index patterns must exist in the same space as your {ml} jobs.
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If {stack} {security-features} are enabled, you must also ensure your users have
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the <<setup-privileges,necessary privileges>>. If the {operator-feature} is
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enabled, there are some {ml} settings that can be updated only by operator users.
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enabled, there are some {ml} settings that can be updated only by operator
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users.
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TIP: The fastest way to get started with {ml-features} is to
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{ess-trial}[start a free 14-day trial of {ess}] in the cloud.
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[[setup-privileges]]
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== Security privileges
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[discrete]
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[[es-security-privileges]]
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=== {es} security privileges
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The {stack-security-features} provide roles and privileges that make it easier
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to control which users can manage or view {ml} objects such as jobs, {dfeeds},
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results, and model snapshots. {kib} also enables you to control access to the
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{ml-features} within each space. You can manage your roles, privileges, and
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spaces in the **{stack-manage-app}** app in {kib}. For more information, see
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{ref}/security-privileges.html[Security privileges] and
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results, and model snapshots.
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If you use {ml} APIs, you must have the `machine_learning_admin` or
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`machine_learning_user` built-in roles or the equivalent cluster privileges and
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the following index privileges:
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For full access:
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* [ ] `read` and `view_index_metadata` on source indices
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* [ ] `read`, `manage`, and `index` on destination indices (for
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{dfanalytics-jobs} only)
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For read-only access:
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* [ ] `read` index privileges on source indices
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* [ ] `read` index privileges on destination indices (for {dfanalytics-jobs}
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only)
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[discrete]
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[[kib-security-privileges]]
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=== {kib} privileges
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In {kib}, the {ml-features} must be visible in your
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{kibana-ref}/xpack-spaces.html#spaces-control-feature-visibility[space] and your
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source index patterns must exist in the same space as your {ml} jobs.
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{kib} enables you to control access to the {ml-features} within each space. You
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can manage your roles, privileges, and spaces in the **{stack-manage-app}** app
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in {kib}. For more information, see
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{ref}/security-privileges.html[Security privileges] and
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{kibana-ref}/kibana-privileges.html[{kib} privileges].
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The `machine_learning_admin` and `machine_learning_user` roles grant access to
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the {ml-features} in all {kib} spaces. Therefore, when you use {kib}, use custom
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roles instead and set your {kib} privileges appropriately for each space.
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For full access to the {ml-features} in {kib}, you must have:
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[%interactive]
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IMPORTANT: You cannot limit access to specific {ml} objects in each space. If
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the {ml} feature is visible in your space and you have `read` or `all` {kib}
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privileges for the feature, you have access to *all* {ml} objects in that space.
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If you do not use {kib} and instead call {ml} APIs directly, you must have the
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index privileges listed above as well as `machine_learning_admin` or `machine_learning_user` built-in roles.
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WARNING: The `machine_learning_admin` and `machine_learning_user` roles grant
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access to the {ml-features} in all {kib} spaces. Therefore, when you use {kib},
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use custom roles instead and set your {kib} privileges appropriately for each
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space.

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