* Adding ESS icons to supported ES settings.
* Adding new file for supported ESS settings.
* Adding supported ESS settings for HTTP and disk-based shard allocation.
* Adding more supported settings for ESS.
* Adding descriptions for each Cloud section, plus additional settings.
* Adding new warehouse file for Cloud, plus additional settings.
* Adding node settings for Cloud.
* Adding audit settings for Cloud.
* Resolving merge conflict.
* Adding SAML settings (part 1).
* Adding SAML realm encryption and signing settings.
* Adding SAML SSL settings.
* Adding Kerberos realm settings.
* Adding OpenID Connect Realm settings.
* Adding OpenID Connect SSL settings.
* Resolving leftover Git merge markers.
* Removing Cloud settings page and link to it.
* Add link to mapping source
* Update docs/reference/docs/reindex.asciidoc
* Incorporate edit of HTTP settings
* Remove "cloud" from tag and ID
* Remove "cloud" from tag and update description
* Remove "cloud" from tag and ID
* Change "whitelists" to "specifies"
* Remove "cloud" from end tag
* Removing cloud from IDs and tags.
* Changing link reference to fix build issue.
* Adding index management page for missing settings.
* Removing warehouse file for Cloud and moving settings elsewhere.
* Clarifying true/false usage of http.detailed_errors.enabled.
* Changing underscore to dash in link to fix ci build.
This adds new plugin level circuit breaker for the ML plugin.
`model_inference` is the circuit breaker qualified name.
Right now it simply adds to the breaker when the model is loaded (and possibly breaking) and removing from the breaker when the model is unloaded.
This change introduces a new setting,
xpack.ml.process_connect_timeout, to enable
the timeout for one of the external ML processes
to connect to the ES JVM to be increased.
The timeout may need to be increased if many
processes are being started simultaneously on
the same machine. This is unlikely in clusters
with many ML nodes, as we balance the processes
across the ML nodes, but can happen in clusters
with a single ML node and a high value for
xpack.ml.node_concurrent_job_allocations.
This change does the following:
1. Makes the per-node setting xpack.ml.max_open_jobs
into a cluster-wide dynamic setting
2. Changes the job node selection to continue to use the
per-node attributes storing the maximum number of open
jobs if any node in the cluster is older than 7.1, and
use the dynamic cluster-wide setting if all nodes are on
7.1 or later
3. Changes the docs to reflect this
4. Changes the thread pools for native process communication
from fixed size to scaling, to support the dynamic nature
of xpack.ml.max_open_jobs
5. Renames the autodetect thread pool to the job comms
thread pool to make clear that it will be used for other
types of ML jobs (data frame analytics in particular)
Backport of #39320
* Adding new xpack.ml.max_lazy_ml_nodes setting to docs
* Fixing docs, making it clearer what the setting does
* Adding note about external process need
Lisa Cawley
Adam Locke
Benjamin Trent
James Rodewig
István Zoltán Szabó
David Roberts