Besides a rename, this changes allows to processor to attach multiple
enrich docs to the document being ingested.
Also in order to control the maximum number of enrich docs to be
included in the document being ingested, the `max_matches` setting
is added to the enrich processor.
Relates #32789
As per #45852 comment we no longer need to log stack-traces in
SecurityTransportExceptionHandler and SecurityHttpExceptionHandler even
if trace logging is enabled.
(cherry picked from commit c99224a32d26db985053b7b36e2049036e438f97)
* [ML][Transforms] fixing stop on changes check bug
* Adding new method finishAndCheckState to cover race conditions in early terminations
* changing stopping conditions in `onStart`
* allow indexer to finish when exiting early
Fixes a problem where operations_behind would be one less than
expected per shard in a new index matched by the data frame
transform source pattern.
For example, if a data frame transform had a source of foo*
and a new index foo-new was created with 2 shards and 7 documents
indexed in it then operations_behind would be 5 prior to this
change.
The problem was that an empty index has a global checkpoint
number of -1 and the sequence number of the first document that
is indexed into an index is 0, not 1. This doesn't matter for
indices included in both the last and next checkpoints, as the
off-by-one errors cancelled, but for a new index it affected
the observed result.
Though we allow CCS within datafeeds, users could prevent nodes from accessing remote clusters. This can cause mysterious errors and difficult to troubleshoot.
This commit adds a check to verify that `cluster.remote.connect` is enabled on the current node when a datafeed is configured with a remote index pattern.
* [ML] Regression dependent variable must be numeric
This adds a validation that the dependent variable of a regression
analysis must be numeric.
* Address review comments and fix some problems
In addition to addressing the review comments, this
commit fixes a few issues I found during testing.
In particular:
- if there were mappings for required fields but they were
not included we were not reporting the error
- if explicitly included fields had unsupported types we were
not reporting the error
Unfortunately, I couldn't get those fixed without refactoring
the code in `ExtractedFieldsDetector`.
This commit adds the `rollover_alias` setting required for ILM to work
correctly to the SLM history index template and adds assertions to the
SLM integration tests to ensure that it works correctly.
Prior to this commit the foreach action execution had a hard coded
limit to 100 iterations. This commit allows the max number of
iterations to be a configuration ('max_iterations') on the foreach
action. The default remains 100.
Adds a parameter `training_percent` to regression. The default
value is `100`. When the parameter is set to a value less than `100`,
from the rows that can be used for training (ie. those that have a
value for the dependent variable) we randomly choose whether to actually
use for training. This enables splitting the data into a training set and
the rest, usually called testing, validation or holdout set, which allows
for validating the model on data that have not been used for training.
Technically, the analytics process considers as training the data that
have a value for the dependent variable. Thus, when we decide a training
row is not going to be used for training, we simply clear the row's
dependent variable.
The existing privilege model for API keys with privileges like
`manage_api_key`, `manage_security` etc. are too permissive and
we would want finer-grained control over the cluster privileges
for API keys. Previously APIs created would also need these
privileges to get its own information.
This commit adds support for `manage_own_api_key` cluster privilege
which only allows api key cluster actions on API keys owned by the
currently authenticated user. Also adds support for retrieval of
the API key self-information when authenticating via API key
without the need for the additional API key privileges.
To support this privilege, we are introducing additional
authentication context along with the request context such that
it can be used to authorize cluster actions based on the current
user authentication.
The API key get and invalidate APIs introduce an `owner` flag
that can be set to true if the API key request (Get or Invalidate)
is for the API keys owned by the currently authenticated user only.
In that case, `realm` and `username` cannot be set as they are
assumed to be the currently authenticated ones.
The changes cover HLRC changes, documentation for the API changes.
Closes#40031
This commit introduces PKI realm delegation. This feature
supports the PKI authentication feature in Kibana.
In essence, this creates a new API endpoint which Kibana must
call to authenticate clients that use certificates in their TLS
connection to Kibana. The API call passes to Elasticsearch the client's
certificate chain. The response contains an access token to be further
used to authenticate as the client. The client's certificates are validated
by the PKI realms that have been explicitly configured to permit
certificates from the proxy (Kibana). The user calling the delegation
API must have the delegate_pki privilege.
Closes#34396
This adds a pipeline aggregation that calculates the cumulative
cardinality of a field. It does this by iteratively merging in the
HLL sketch from consecutive buckets and emitting the cardinality up
to that point.
This is useful for things like finding the total "new" users that have
visited a website (as opposed to "repeat" visitors).
This is a Basic+ aggregation and adds a new Data Science plugin
to house it and future advanced analytics/data science aggregations.
Today if non-TLS record is received on TLS port generic exception will
be logged with the stack-trace.
SSLExceptionHelper.isNotSslRecordException method does not work because
it's assuming that NonSslRecordException would be top-level.
This commit addresses the issue and the log would be more concise.
(cherry picked from commit 6b83527bf0c23d4d5b97fab7f290c43432945d4f)
This commit allows the Transport Actions for the SSO realms to
indicate the realm that should be used to authenticate the
constructed AuthenticationToken. This is useful in the case that
many authentication realms of the same type have been configured
and where the caller of the API(Kibana or a custom web app) already
know which realm should be used so there is no need to iterate all
the realms of the same type.
The realm parameter is added in the relevant REST APIs as optional
so as not to introduce any breaking change.
Previously, the stats API reports a progress percentage
for DF analytics tasks that are running and are in the
`reindexing` or `analyzing` state.
This means that when the task is `stopped` there is no progress
reported. Thus, one cannot distinguish between a task that never
run to one that completed.
In addition, there are blind spots in the progress reporting.
In particular, we do not account for when data is loaded into the
process. We also do not account for when results are written.
This commit addresses the above issues. It changes progress
to being a list of objects, each one describing the phase
and its progress as a percentage. We currently have 4 phases:
reindexing, loading_data, analyzing, writing_results.
When the task stops, progress is persisted as a document in the
state index. The stats API now reports progress from in-memory
if the task is running, or returns the persisted document
(if there is one).
A policy type controls how the enrich index is created and
the query executed against the match field. Currently there
is a single policy type (`exact_match`). In the near future
more policy types will be added and different policy may have
different configuration options.
For this reason type should be a json object instead of a string field:
```
{
"exact_match": {
...
}
}
```
instead of:
```
{
"type": "exact_match",
...
}
```
This will make streaming parsing of enrich policies easier as in the
new format, the parsing code can know ahead what configuration fields
to expect. In the latter format that is not possible if the type field
appears not as the first field.
Relates to #32789
The security indices were being created without specifying the
refresh interval, which means it would inherit a value from any
templates that exists.
However, certain security functionality depends on being able to
wait_for refresh, and causes errors (e.g. in Kibana) if that time
exceeds 30s.
This commit changes the security indices configuration to always be
created with a 1s refresh interval. This prevents any templates from
inadvertantly interfering with the proper functioning of security.
It is possible for an administrator to explicitly change the refresh
interval after the indices have been created.
Backport of: #45434
This change adds a new SSL context
xpack.notification.email.ssl.*
that supports the standard SSL configuration settings (truststore,
verification_mode, etc). This SSL context is used when configuring
outbound SMTP properties for watcher email notifications.
Backport of: #45272
* [ML] Adding data frame analytics stats to _usage API (#45820)
* [ML] Adding data frame analytics stats to _usage API
* making the size of analytics stats 10k
* adjusting backport
Adds index versioning for the internal data frame transform index. Allows for new indices to be created and referenced, `GET` requests now query over the index pattern and takes the latest doc (based on INDEX name).
Following our own guidelines, SLM should use rollover instead of purely
time-based indices to keep shard counts low. This commit implements lazy
index creation for SLM's history indices, indexing via an alias, and
rollover in the built-in ILM policy.
Regression analysis support missing fields. Even more, it is expected
that the dependent variable has missing fields to the part of the
data frame that is not for training.
This commit allows to declare that an analysis supports missing values.
For such analysis, rows with missing values are not skipped. Instead,
they are written as normal with empty strings used for the missing values.
This also contains a fix to the integration test.
Closes#45425
* [ML] better handle empty results when evaluating regression
* adding new failure test to ml_security black list
* fixing equality check for regression results
The get and list APIs are a single API in this commit. Whether
requesting one named policy or all policies, a list of policies is
returened. The list API code has all been removed and the GET api is
what remains, which contains much of the list response code.
* [ML][Data frame] fixing failure state transitions and race condition (#45627)
There is a small window for a race condition while we are flagging a task as failed.
Here are the steps where the race condition occurs:
1. A failure occurs
2. Before `AsyncTwoPhaseIndexer` calls the `onFailure` handler it does the following:
a. `finishAndSetState()` which sets the IndexerState to STARTED
b. `doSaveState(...)` which attempts to save the current state of the indexer
3. Another trigger is fired BEFORE `onFailure` can fire, but AFTER `finishAndSetState()` occurs.
The trick here is that we will eventually set the indexer to failed, but possibly not before another trigger had the opportunity to fire. This could obviously cause some weird state interactions. To combat this, I have put in some predicates to verify the state before taking actions. This is so if state is indeed marked failed, the "second trigger" stops ASAP.
Additionally, I move the task state checks INTO the `start` and `stop` methods, which will now require a `force` parameter. `start`, `stop`, `trigger` and `markAsFailed` are all `synchronized`. This should gives us some guarantees that one will not switch states out from underneath another.
I also flag the task as `failed` BEFORE we successfully write it to cluster state, this is to allow us to make the task fail more quickly. But, this does add the behavior where the task is "failed" but the cluster state does not indicate as much. Adding the checks in `start` and `stop` will handle this "real state vs cluster state" race condition. This has always been a problem for `_stop` as it is not a master node action and doesn’t always have the latest cluster state.
closes#45609
Relates to #45562
* [ML][Data Frame] moves failure state transition for MT safety (#45676)
* [ML][Data Frame] moves failure state transition for MT safety
* removing unused imports
* Introduce Spatial Plugin (#44389)
Introduce a skeleton Spatial plugin that holds new licensed features coming to
Geo/Spatial land!
* [GEO] Refactor DeprecatedParameters in AbstractGeometryFieldMapper (#44923)
Refactor DeprecatedParameters specific to legacy geo_shape out of
AbstractGeometryFieldMapper.TypeParser#parse.
* [SPATIAL] New ShapeFieldMapper for indexing cartesian geometries (#44980)
Add a new ShapeFieldMapper to the xpack spatial module for
indexing arbitrary cartesian geometries using a new field type called shape.
The indexing approach leverages lucene's new XYShape field type which is
backed by BKD in the same manner as LatLonShape but without the WGS84
latitude longitude restrictions. The new field mapper builds on and
extends the refactoring effort in AbstractGeometryFieldMapper and accepts
shapes in either GeoJSON or WKT format (both of which support non geospatial
geometries).
Tests are provided in the ShapeFieldMapperTest class in the same manner
as GeoShapeFieldMapperTests and LegacyGeoShapeFieldMapperTests.
Documentation for how to use the new field type and what parameters are
accepted is included. The QueryBuilder for searching indexed shapes is
provided in a separate commit.
* [SPATIAL] New ShapeQueryBuilder for querying indexed cartesian geometry (#45108)
Add a new ShapeQueryBuilder to the xpack spatial module for
querying arbitrary Cartesian geometries indexed using the new shape field
type.
The query builder extends AbstractGeometryQueryBuilder and leverages the
ShapeQueryProcessor added in the previous field mapper commit.
Tests are provided in ShapeQueryTests in the same manner as
GeoShapeQueryTests and docs are updated to explain how the query works.
The current implementations make it difficult for
adding new privileges (example: a cluster privilege which is
more than cluster action-based and not exposed to the security
administrator). On the high level, we would like our cluster privilege
either:
- a named cluster privilege
This corresponds to `cluster` field from the role descriptor
- or a configurable cluster privilege
This corresponds to the `global` field from the role-descriptor and
allows a security administrator to configure them.
Some of the responsibilities like the merging of action based cluster privileges
are now pushed at cluster permission level. How to implement the predicate
(using Automaton) is being now enforced by cluster permission.
`ClusterPermission` helps in enforcing the cluster level access either by
performing checks against cluster action and optionally against a request.
It is a collection of one or more permission checks where if any of the checks
allow access then the permission allows access to a cluster action.
Implementations of cluster privilege must be able to provide information
regarding the predicates to the cluster permission so that can be enforced.
This is enforced by making implementations of cluster privilege aware of
cluster permission builder and provide a way to specify how the permission is
to be built for a given privilege.
This commit renames `ConditionalClusterPrivilege` to `ConfigurableClusterPrivilege`.
`ConfigurableClusterPrivilege` is a renderable cluster privilege exposed
as a `global` field in role descriptor.
Other than this there is a requirement where we would want to know if a cluster
permission is implied by another cluster-permission (`has-privileges`).
This is helpful in addressing queries related to privileges for a user.
This is not just simply checking of cluster permissions since we do not
have access to runtime information (like request object).
This refactoring does not try to address those scenarios.
Relates #44048
