[DOCS] Document static machine learning settings (#61382)

docs/reference/settings/ml-settings.asciidoc

@@ -10,15 +10,9 @@
 // tag::ml-settings-description-tag[]
 You do not need to configure any settings to use {ml}. It is enabled by default.
 
-IMPORTANT: {ml-cap} uses SSE4.2 instructions, so will only work on machines whose
-CPUs {wikipedia}/SSE4#Supporting_CPUs[support] SSE4.2. If you
-run {es} on older hardware you must disable {ml} (by setting `xpack.ml.enabled`
-to `false`).
-
-All of these settings can be added to the `elasticsearch.yml` configuration 
-file. The dynamic settings can also be updated across a cluster with the
-<<cluster-update-settings,cluster update settings API>>. Dynamic settings take 
-precedence over settings in the `elasticsearch.yml` file.
+IMPORTANT: {ml-cap} uses SSE4.2 instructions, so it works only on machines whose
+CPUs {wikipedia}/SSE4#Supporting_CPUs[support] SSE4.2. If you run {es} on older
+hardware, you must disable {ml} (by setting `xpack.ml.enabled` to `false`).
 
 // end::ml-settings-description-tag[]
 
@@ -27,8 +21,9 @@ precedence over settings in the `elasticsearch.yml` file.
 ==== General machine learning settings
 
 `node.roles: [ ml ]`::
-Set `node.roles` to contain `ml` to identify the node as a _{ml} node_ that is 
-capable of running jobs. Every node is a {ml} node by default.+
+(<<static-cluster-setting,Static>>) Set `node.roles` to contain `ml` to identify
+the node as a _{ml} node_ that is capable of running jobs. Every node is a {ml}
+node by default.
 +
 If you use the `node.roles` setting, then all required roles must be explicitly  
 set. Consult <<modules-node>> to learn more.
@@ -38,7 +33,8 @@ the `ml` role.
 
 
 `xpack.ml.enabled`::
-Set to `true` (default) to enable {ml} APIs on the node.
+(<<static-cluster-setting,Static>>) Set to `true` (default) to enable {ml} APIs
+on the node.
 +
 If set to `false`, the {ml} APIs are disabled on the node. Therefore the node
 cannot open jobs, start {dfeeds}, or receive transport (internal) communication
@@ -54,58 +50,62 @@ want to use {ml-features} in clients or {kib}, it must also be enabled on all
 coordinating nodes.
 
 `xpack.ml.inference_model.cache_size`::
-The maximum inference cache size allowed. The inference cache exists in the JVM
-heap on each ingest node. The cache affords faster processing times for the
-`inference` processor. The value can be a static byte sized value (i.e. "2gb")
-or a percentage of total allocated heap. The default is "40%".
-See also <<model-inference-circuit-breaker>>.
+(<<static-cluster-setting,Static>>) The maximum inference cache size allowed.
+The inference cache exists in the JVM heap on each ingest node. The cache
+affords faster processing times for the `inference` processor. The value can be
+a static byte sized value (i.e. "2gb") or a percentage of total allocated heap.
+The default is "40%". See also <<model-inference-circuit-breaker>>.
 
 [[xpack-interference-model-ttl]]
 // tag::interference-model-ttl-tag[]
 `xpack.ml.inference_model.time_to_live` {ess-icon}::
-The time to live (TTL) for models in the inference model cache. The TTL is
-calculated from last access. The `inference` processor attempts to load the
-model from cache. If the `inference` processor does not receive any documents
-for the duration of the TTL, the referenced model is flagged for eviction from
-the cache. If a document is processed later, the model is again loaded into the
-cache. Defaults to `5m`.
+(<<static-cluster-setting,Static>>) The time to live (TTL) for models in the
+inference model cache. The TTL is calculated from last access. The `inference`
+processor attempts to load the model from cache. If the `inference` processor
+does not receive any documents for the duration of the TTL, the referenced model
+is flagged for eviction from the cache. If a document is processed later, the
+model is again loaded into the cache. Defaults to `5m`.
 // end::interference-model-ttl-tag[]
 
-`xpack.ml.max_inference_processors` (<<cluster-update-settings,Dynamic>>)::
-The total number of `inference` type processors allowed across all ingest
-pipelines. Once the limit is reached, adding an `inference` processor to
-a pipeline is disallowed. Defaults to `50`.
-
-`xpack.ml.max_machine_memory_percent` (<<cluster-update-settings,Dynamic>>)::
-The maximum percentage of the machine's memory that {ml} may use for running
-analytics processes. (These processes are separate to the {es} JVM.) Defaults to
-`30` percent. The limit is based on the total memory of the machine, not current
-free memory. Jobs will not be allocated to a node if doing so would cause the
-estimated memory use of {ml} jobs to exceed the limit.
-
-`xpack.ml.max_model_memory_limit` (<<cluster-update-settings,Dynamic>>)::
-The maximum `model_memory_limit` property value that can be set for any job on
-this node. If you try to create a job with a `model_memory_limit` property value
-that is greater than this setting value, an error occurs. Existing jobs are not
-affected when you update this setting. For more information about the
-`model_memory_limit` property, see <<put-analysislimits>>.
+`xpack.ml.max_inference_processors`::
+(<<cluster-update-settings,Dynamic>>) The total number of `inference` type
+processors allowed across all ingest pipelines. Once the limit is reached,
+adding an `inference` processor to a pipeline is disallowed. Defaults to `50`.
+
+`xpack.ml.max_machine_memory_percent`::
+(<<cluster-update-settings,Dynamic>>) The maximum percentage of the machine's
+memory that {ml} may use for running analytics processes. (These processes are
+separate to the {es} JVM.) Defaults to `30` percent. The limit is based on the
+total memory of the machine, not current free memory. Jobs are not allocated to
+a node if doing so would cause the estimated memory use of {ml} jobs to exceed
+the limit.
+
+`xpack.ml.max_model_memory_limit`::
+(<<cluster-update-settings,Dynamic>>) The maximum `model_memory_limit` property
+value that can be set for any job on this node. If you try to create a job with
+a `model_memory_limit` property value that is greater than this setting value,
+an error occurs. Existing jobs are not affected when you update this setting.
+For more information about the `model_memory_limit` property, see
+<<put-analysislimits>>.
 
 [[xpack.ml.max_open_jobs]]
-`xpack.ml.max_open_jobs` (<<cluster-update-settings,Dynamic>>)::
-The maximum number of jobs that can run simultaneously on a node. Defaults to
-`20`. In this context, jobs include both {anomaly-jobs} and {dfanalytics-jobs}.
-The maximum number of jobs is also constrained by memory usage. Thus if the
-estimated memory usage of the jobs would be higher than allowed, fewer jobs will
-run on a node. Prior to version 7.1, this setting was a per-node non-dynamic
-setting. It became a cluster-wide dynamic setting in version 7.1. As a result,
-changes to its value after node startup are used only after every node in the
-cluster is running version 7.1 or higher. The maximum permitted value is `512`.
-
-`xpack.ml.node_concurrent_job_allocations` (<<cluster-update-settings,Dynamic>>)::
-The maximum number of jobs that can concurrently be in the `opening` state on
-each node. Typically, jobs spend a small amount of time in this state before
-they move to `open` state. Jobs that must restore large models when they are
-opening spend more time in the `opening` state. Defaults to `2`.
+`xpack.ml.max_open_jobs`::
+(<<cluster-update-settings,Dynamic>>) The maximum number of jobs that can run 
+simultaneously on a node. Defaults to `20`. In this context, jobs include both
+{anomaly-jobs} and {dfanalytics-jobs}. The maximum number of jobs is also
+constrained by memory usage. Thus if the estimated memory usage of the jobs
+would be higher than allowed, fewer jobs will run on a node. Prior to version
+7.1, this setting was a per-node non-dynamic setting. It became a cluster-wide
+dynamic setting in version 7.1. As a result, changes to its value after node
+startup are used only after every node in the cluster is running version 7.1 or
+higher. The maximum permitted value is `512`.
+
+`xpack.ml.node_concurrent_job_allocations`::
+(<<cluster-update-settings,Dynamic>>) The maximum number of jobs that can
+concurrently be in the `opening` state on each node. Typically, jobs spend a
+small amount of time in this state before they move to `open` state. Jobs that
+must restore large models when they are opening spend more time in the `opening`
+state. Defaults to `2`.
 
 [discrete]
 [[advanced-ml-settings]]
@@ -114,52 +114,55 @@ opening spend more time in the `opening` state. Defaults to `2`.
 These settings are for advanced use cases; the default values are generally
 sufficient:
 
-`xpack.ml.enable_config_migration` (<<cluster-update-settings,Dynamic>>)::
-Reserved.
+`xpack.ml.enable_config_migration`::
+(<<cluster-update-settings,Dynamic>>) Reserved.
 
-`xpack.ml.max_anomaly_records` (<<cluster-update-settings,Dynamic>>)::
-The maximum number of records that are output per bucket. The default value is
-`500`.
+`xpack.ml.max_anomaly_records`::
+(<<cluster-update-settings,Dynamic>>) The maximum number of records that are
+output per bucket. The default value is `500`.
 
-`xpack.ml.max_lazy_ml_nodes` (<<cluster-update-settings,Dynamic>>)::
-The number of lazily spun up Machine Learning nodes. Useful in situations
-where ML nodes are not desired until the first Machine Learning Job
-is opened. It defaults to `0` and has a maximum acceptable value of `3`.
-If the current number of ML nodes is `>=` than this setting, then it is
+`xpack.ml.max_lazy_ml_nodes`::
+(<<cluster-update-settings,Dynamic>>) The number of lazily spun up {ml} nodes.
+Useful in situations where {ml} nodes are not desired until the first {ml} job
+opens. It defaults to `0` and has a maximum acceptable value of `3`. If the
+current number of {ml} nodes is greater than or equal to this setting, it is
 assumed that there are no more lazy nodes available as the desired number
-of nodes have already been provisioned. When a job is opened with this
-setting set at `>0` and there are no nodes that can accept the job, then
-the job will stay in the `OPENING` state until a new ML node is added to the
-cluster and the job is assigned to run on that node.
+of nodes have already been provisioned. If a job is opened and this setting has
+a value greater than zero and there are no nodes that can accept the job, the
+job stays in the `OPENING` state until a new {ml} node is added to the cluster
+and the job is assigned to run on that node.
 +
-IMPORTANT: This setting assumes some external process is capable of adding ML nodes
-to the cluster. This setting is only useful when used in conjunction with
+IMPORTANT: This setting assumes some external process is capable of adding {ml}
+nodes to the cluster. This setting is only useful when used in conjunction with
 such an external process.
 
-`xpack.ml.process_connect_timeout` (<<cluster-update-settings,Dynamic>>)::
-The connection timeout for {ml} processes that run separately from the {es} JVM.
-Defaults to `10s`. Some {ml} processing is done by processes that run separately
-to the {es} JVM. When such processes are started they must connect to the {es}
-JVM. If such a process does not connect within the time period specified by this
-setting then the process is assumed to have failed. Defaults to `10s`. The minimum
-value for this setting is `5s`.
+`xpack.ml.process_connect_timeout`::
+(<<cluster-update-settings,Dynamic>>) The connection timeout for {ml} processes
+that run separately from the {es} JVM. Defaults to `10s`. Some {ml} processing
+is done by processes that run separately to the {es} JVM. When such processes
+are started they must connect to the {es} JVM. If such a process does not
+connect within the time period specified by this setting then the process is
+assumed to have failed. Defaults to `10s`. The minimum value for this setting is
+`5s`.
 
 [discrete]
 [[model-inference-circuit-breaker]]
 ==== {ml-cap} circuit breaker settings
 
-`breaker.model_inference.limit` (<<cluster-update-settings,Dynamic>>)::
-Limit for the model inference breaker, which defaults to 50% of the JVM heap.
-If the parent circuit breaker is less than 50% of the JVM heap, it is bound
-to that limit instead. See <<circuit-breaker>>.
+`breaker.model_inference.limit`::
+(<<cluster-update-settings,Dynamic>>) Limit for the model inference breaker,
+which defaults to 50% of the JVM heap. If the parent circuit breaker is less
+than 50% of the JVM heap, it is bound to that limit instead. See
+<<circuit-breaker>>.
 
-`breaker.model_inference.overhead` (<<cluster-update-settings,Dynamic>>)::
-A constant that all accounting estimations are multiplied by to determine
-a final estimation. Defaults to 1. See <<circuit-breaker>>.
+`breaker.model_inference.overhead`::
+(<<cluster-update-settings,Dynamic>>) A constant that all accounting estimations
+are multiplied by to determine a final estimation. Defaults to 1. See
+<<circuit-breaker>>.
 
 `breaker.model_inference.type`::
-The underlying type of the circuit breaker. There are two valid options: `noop`
-and `memory`. `noop` means the circuit breaker does nothing to prevent too much
-memory usage. `memory` means the circuit breaker tracks the memory used by
-inference models and can potentially break and prevent OutOfMemory errors. The
-default is `memory`.
+(<<static-cluster-setting,Static>>) The underlying type of the circuit breaker.
+There are two valid options: `noop` and `memory`. `noop` means the circuit
+breaker does nothing to prevent too much memory usage. `memory` means the
+circuit breaker tracks the memory used by inference models and can potentially
+break and prevent `OutOfMemory` errors. The default is `memory`.

docs/reference/settings/transform-settings.asciidoc

@@ -10,11 +10,6 @@
 You do not need to configure any settings to use {transforms}. It is enabled by
 default.
 
-All of these settings can be added to the `elasticsearch.yml` configuration file.
-The dynamic settings can also be updated across a cluster with the
-<<cluster-update-settings,cluster update settings API>>. Dynamic settings take
-precedence over settings in the `elasticsearch.yml` file.
-
 [discrete]
 [[general-transform-settings]]
 ==== General {transforms} settings