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<titleabbrev>Setup and security</titleabbrev>
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++++
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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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-
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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.
@@ -37,14 +34,48 @@ information, see {ref}/modules-node.html#ml-node[{ml-cap} nodes] and
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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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+
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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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+
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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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+
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+ For full access:
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+
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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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+
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+ For read-only access:
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+
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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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+
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+ [discrete]
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+ [[kib-security-privileges]]
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+ === {kib} privileges
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+
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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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+
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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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+
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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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-
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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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-
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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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