Add validation for the following logfile audit settings:
xpack.security.audit.logfile.events.include
xpack.security.audit.logfile.events.exclude
xpack.security.audit.logfile.events.ignore_filters.*.users
xpack.security.audit.logfile.events.ignore_filters.*.realms
xpack.security.audit.logfile.events.ignore_filters.*.roles
xpack.security.audit.logfile.events.ignore_filters.*.indices
Closes#52357
Relates #47711#47038
Follows the example from #47246
When a license expires, or license state changes, functionality might be
disabled. This commit adds messages for CCR to inform users that CCR
functionality will be disabled when a license expires, or when license
state changes to a license level lower than trial/platinum/enterprise.
This adds machine learning model feature importance calculations to the inference processor.
The new flag in the configuration matches the analytics parameter name: `num_top_feature_importance_values`
Example:
```
"inference": {
"field_mappings": {},
"model_id": "my_model",
"inference_config": {
"regression": {
"num_top_feature_importance_values": 3
}
}
}
```
This will write to the document as follows:
```
"inference" : {
"feature_importance" : {
"FlightTimeMin" : -76.90955548511226,
"FlightDelayType" : 114.13514762158526,
"DistanceMiles" : 13.731580450792187
},
"predicted_value" : 108.33165831875137,
"model_id" : "my_model"
}
```
This is done through calculating the [SHAP values](https://arxiv.org/abs/1802.03888).
It requires that models have populated `number_samples` for each tree node. This is not available to models that were created before 7.7.
Additionally, if the inference config is requesting feature_importance, and not all nodes have been upgraded yet, it will not allow the pipeline to be created. This is to safe-guard in a mixed-version environment where only some ingest nodes have been upgraded.
NOTE: the algorithm is a Java port of the one laid out in ml-cpp: https://github.com/elastic/ml-cpp/blob/master/lib/maths/CTreeShapFeatureImportance.cc
usability blocked by: https://github.com/elastic/ml-cpp/pull/991
This commit renames ElasticsearchAssertions#assertThrows to
assertRequestBuilderThrows and assertFutureThrows to avoid a
naming clash with JUnit 4.13+ and static imports of these methods.
Additionally, these methods have been updated to make use of
expectThrows internally to avoid duplicating the logic there.
Relates #51787
Backport of #52582
This commit modifies the codebase so that our production code uses a
single instance of the IndexNameExpressionResolver class. This change
is being made in preparation for allowing name expression resolution
to be augmented by a plugin.
In order to remove some instances of IndexNameExpressionResolver, the
single instance is added as a parameter of Plugin#createComponents and
PersistentTaskPlugin#getPersistentTasksExecutor.
Backport of #52596
The top_metrics test assumed that it'd never end up *only* reducing
unmapped results. But, rarely, it does. This handles that case in the
test.
Closes#52462
* Make FreezeStep retryable
This change marks `FreezeStep` as retryable and adds test to make sure we can really run it again.
* refactor tests
Co-authored-by: Elastic Machine <elasticmachine@users.noreply.github.com>
* Refactor Inflexible Snapshot Repository BwC (#52365)
Transport the version to use for a snapshot instead of whether to use shard generations in the snapshots in progress entry. This allows making upcoming repository metadata changes in a flexible manner in an analogous way to how we handle serialization BwC elsewhere.
Also, exposing the version at the repository API level will make it easier to do BwC relevant changes in derived repositories like source only or encrypted.
Add enterprise operation mode to properly map enterprise license.
Aslo refactor XPackLicenstate class to consolidate license status and mode checks.
This class has many sychronised methods to check basically three things:
* Minimum operation mode required
* Whether security is enabled
* Whether current license needs to be active
Depends on the actual feature, either 1, 2 or all of above checks are performed.
These are now consolidated in to 3 helper methods (2 of them are new).
The synchronization is pushed down to the helper methods so actual checking
methods no longer need to worry about it.
resolves: #51081
When `PUT` is called to store a trained model, it is useful to return the newly create model config. But, it is NOT useful to return the inflated definition.
These definitions can be large and returning the inflated definition causes undo work on the server and client side.
Co-authored-by: Elastic Machine <elasticmachine@users.noreply.github.com>
This adds `_all` to Calendar searches. This enables users to supply the `_all` string in the `job_ids` array when creating a Calendar. That calendar will now be applied to all jobs (existing and newly created).
Closes#45013
Co-authored-by: Elastic Machine <elasticmachine@users.noreply.github.com>
This commit updates the enrich.get_policy API to specify name
as a list, in line with other URL parts that accept a comma-separated
list of values.
In addition, update the get enrich policy API docs
to align the URL part name in the documentation with
the name used in the REST API specs.
(cherry picked from commit 94f6f946ef283dc93040e052b4676c5bc37f4bde)
* Make DeleteStep retryable
This change marks `DeleteStep` as retryable and adds test to make sure we really can invoke it again.
* Fix unused import
* revert unneeded changes
* test reworked
This commit adds more logging to the actions that the SLM retention task does. It will help in the
event that we need to diagnose any additional issues or problems while running retention.
This changes the tree validation code to ensure no node in the tree has a
feature index that is beyond the bounds of the feature_names array.
Specifically this handles the situation where the C++ emits a tree containing
a single node and an empty feature_names list. This is valid tree used to
centre the data in the ensemble but the validation code would reject this
as feature_names is empty. This meant a broken workflow as you cannot GET
the model and PUT it back
Currently we used the secure random number generate when generating http
request ids in the security AuditUtil. We do not need to be using this
level of randomness for this use case. Additionally, this random number
generator involves locking that blocks the http worker threads at high
concurrency loads.
This commit modifies this randomness generator to use our reproducible
randomness generator for Elasticsearch. This generator will fall back to
thread local random when used in production.
This is useful in cases where the caller of the API needs to know
the name of the realm that consumed the SAML Response and
authenticated the user and this is not self evident (i.e. because
there are many saml realms defined in ES).
Currently, the way to learn the realm name would be to make a
subsequent request to the `_authenticate` API.
When changing a job state using a mechanism that doesn't
wait for the desired state to be reached within the production
code the test code needs to loop until the cluster state has
been updated.
Closes#52451
Backport from #52179
Don't rely on the delete index api to resolve all the enrich indices for a particular enrich policy using a '[policy_name]-*' wildcard expression. With this change, the delete policy api will resolve the indices to remove and pass that directly to the delete index api.
This resolves a bug, that if `action.destructive_requires_name` setting has been set to true then the delete policy api is unable to remove the enrich indices related to the policy being deleted.
Closes#51228
Co-authored-by: bellengao <gbl_long@163.com>
audit messages are stored in the notifications index, so audit information is lost for integration
tests. This change forwards audit messages to logs, so they can help to debug issues.
relates: #51627
Following the change to store cluster state in Lucene indices
(#50907) it can take longer for all the cluster state updates
associated with node failure scenarios to be processed during
internal cluster tests where several nodes all run in the same
JVM.
Refactor the code to allow contextual parameterization of dateFormat and
name.
Separate aggs/query implementation though there's room for improvement
in the future
(cherry picked from commit e086f81b688875b33d01e4504ce7377031c8cf28)
The shard follow task cleaner executes on behalf of the user to clean up
a shard follow task after the follower index has been
deleted. Otherwise, these persistent tasks are left laying around, and
they fail to execute because the follower index has been deleted. In the
face of security, attempts to complete these persistent tasks would
fail. This is because these cleanups are executed under the system
context (this makes sense, they are happening on behalf of the user
after the user has executed an action) but the system role was never
granted the permission for persistent task completion. This commit
addresses this by adding this cluster privilege to the system role.
We marked the `init` ILM step as retryable but our test used `waitUntil`
without an assert so we didn’t catch the fact that we were not actually
able to retry this step as our ILM state didn’t contain any information
about the policy execution (as we were in the process of initialising
it).
This commit manually sets the current step to `init` when we’re moving
the ilm policy into the ERROR step (this enables us to successfully
move to the error step and later retry the step)
* ShrunkenIndexCheckStep: Use correct logger
(cherry picked from commit f78d4b3d91345a2a8fc0f48b90dd66c9959bd7ff)
Signed-off-by: Andrei Dan <andrei.dan@elastic.co>
Translate to an agg query even if only literals are selected,
so that the correct number of rows is returned (number of buckets).
Fix issue with key only in GROUP BY (not in select) and WHERE clause:
Resolve aggregates and groupings based on the child plan which holds
the info info for all the fields of the underlying table.
Fixes: #41951Fixes: #41413
(cherry picked from commit 45b85809678b34a448639a420b97e25436ae851f)
The `top_metrics` agg is kind of like `top_hits` but it only works on
doc values so it *should* be faster.
At this point it is fairly limited in that it only supports a single,
numeric sort and a single, numeric metric. And it only fetches the "very
topest" document worth of metric. We plan to support returning a
configurable number of top metrics, requesting more than one metric and
more than one sort. And, eventually, non-numeric sorts and metrics. The
trick is doing those things fairly efficiently.
Co-Authored by: Zachary Tong <zach@elastic.co>
David Kyle
Albert Zaharovits
Ignacio Vera
Martijn van Groningen
Yang Wang
Jason Tedor
Benjamin Trent
Jay Modi
Jack Conradson
Lisa Cawley
Nik Everett
Igor Motov
Hendrik Muhs
markharwood
Przemko Robakowski
Armin Braun
Przemysław Witek
Andrei Stefan
Russ Cam
Ryan Ernst
Lee Hinman
Tim Brooks
Ioannis Kakavas
Henning Andersen
David Roberts
Nhat Nguyen
Costin Leau
Andrei Dan
Hicham Mallah