[DOCS] Simplify ML upgrade step (#40006)

docs/reference/upgrade/close-ml.asciidoc

@@ -11,33 +11,35 @@ POST _ml/set_upgrade_mode?enabled=false
 // TEARDOWN
 ////////////
 
-If your {ml} indices were created earlier than the previous major version, they
-must be reindexed. In those circumstances, there must be no machine learning
-jobs running during the upgrade.
+If your {ml} indices were created before {prev-major-version}, you must
+<<reindex-upgrade,reindex the indices>>.
 
-In all other circumstances, there is no requirement to close your {ml} jobs.
-There are, however, advantages to doing so. If you choose to leave your jobs
-running during the upgrade, they are affected when you stop the {ml} nodes. The
-jobs move to another {ml} node and restore the model states. This scenario has
-the least disruption to the active {ml} jobs but incurs the highest load on the
-cluster.
+If your {ml} indices were created in {prev-major-version}, you can:
 
-To close all {ml} jobs before you upgrade, see
-{stack-ov}/stopping-ml.html[Stopping {ml}]. This method persists the model
-state at the moment of closure, which means that when you open your jobs after
-the upgrade, they use the exact same model. This scenario takes the most time,
-however, especially if you have many jobs or jobs with large model states.
-
-To temporarily halt the tasks associated with your {ml} jobs and {dfeeds} and
-prevent new jobs from opening, use the <<ml-set-upgrade-mode,set upgrade mode API>>:
+* Leave your {ml} jobs running during the upgrade. When you shut down a
+{ml} node, its jobs automatically move to another node and restore the model
+states. This option enables your jobs to continue running during the upgrade but
+it puts increased load on the cluster.
 
+* Temporarily halt the tasks associated with your {ml} jobs and {dfeeds} and
+prevent new jobs from opening by using the
+<<ml-set-upgrade-mode,set upgrade mode API>>:
++
+--
 [source,js]
 --------------------------------------------------
 POST _ml/set_upgrade_mode?enabled=true
 --------------------------------------------------
 // CONSOLE
 
-This method does not persist the absolute latest model state, rather it uses the
-last model state that was automatically saved. By halting the tasks, you avoid
-incurring the cost of managing active jobs during the upgrade and it's quicker
-than stopping {dfeeds} and closing jobs.
+When you disable upgrade mode, the jobs resume using the last model
+state that was automatically saved. This option avoids the overhead of managing
+active jobs during the upgrade and is faster than explicitly stopping {dfeeds}
+and closing jobs.
+--
+
+* {stack-ov}/stopping-ml.html[Stop all {dfeeds} and close all jobs]. This option
+saves the model state at the time of closure. When you reopen the jobs after the
+upgrade, they use the exact same model. However, saving the latest model state
+takes longer than using upgrade mode, especially if you have a lot of jobs or
+jobs with large model states.

docs/reference/upgrade/cluster_restart.asciidoc

@@ -26,7 +26,7 @@ recovery.
 include::synced-flush.asciidoc[]
 --
 
-. *Stop any machine learning jobs that are running.*
+. *Temporarily stop the tasks associated with active {ml} jobs and {dfeeds}.* (Optional)
 +
 --
 include::close-ml.asciidoc[]

docs/reference/upgrade/reindex_upgrade.asciidoc

@@ -59,9 +59,10 @@ ifdef::include-xpack[]
 [TIP]
 ====
 If you use {ml-features} and your {ml} indices were created before
-{prev-major-version}, you must
-{stack-ov}/stopping-ml.html[stop all {dfeeds} and close all {ml} jobs] before
-you reindex the indices.
+{prev-major-version}, you must temporarily halt the tasks associated with your
+{ml} jobs and {dfeeds} and prevent new jobs from opening during the reindex. Use
+the <<ml-set-upgrade-mode,set upgrade mode API>> or
+{stack-ov}/stopping-ml.html[stop all {dfeeds} and close all {ml} jobs].
 
 If you use {es} {security-features}, before you reindex `.security*` internal
 indices it is a good idea to create a temporary superuser account in the `file`
@@ -112,6 +113,17 @@ indices from the previous major version to be upgraded to the
 current major version. Skipping a major version means that you must
 resolve any backward compatibility issues yourself.
 
+ifdef::include-xpack[]
+If you use {ml-features} and you're migrating indices from a 6.5 or earlier
+cluster, the job and {dfeed} configuration information are not stored in an
+index. You must recreate your {ml} jobs in the new cluster. If you are migrating
+from a 6.6 or later cluster, it is a good idea to temporarily halt the tasks
+associated with your {ml} jobs and {dfeeds} to prevent inconsistencies between
+different {ml} indices that are reindexed at slightly different times. Use the
+<<ml-set-upgrade-mode,set upgrade mode API>> or 
+{stack-ov}/stopping-ml.html[stop all {dfeeds} and close all {ml} jobs].
+endif::include-xpack[]
+
 =============================================
 
 To migrate your indices:
@@ -184,4 +196,4 @@ monitor progress of the reindex job with the <<tasks,task API>>:
   `30s` and `1`).
 
 .. Once reindexing is complete and the status of the new index is `green`,
-  you can delete the old index.
+  you can delete the old index.

docs/reference/upgrade/rolling_upgrade.asciidoc

@@ -35,7 +35,7 @@ include::synced-flush.asciidoc[]
 
 --
 
-. *Stop any machine learning jobs that are running.*
+. *Temporarily stop the tasks associated with active {ml} jobs and {dfeeds}.* (Optional)
 +
 --
 include::close-ml.asciidoc[]