This commit adds a deprecation warning when starting
a node where either of the server contexts
(xpack.security.transport.ssl and xpack.security.http.ssl)
meet either of these conditions:
1. The server lacks a certificate/key pair (i.e. neither
ssl.keystore.path not ssl.certificate are configured)
2. The server has some ssl configuration, but ssl.enabled is not
specified. This new validation does not care whether ssl.enabled is
true or false (though other validation might), it simply makes it
an error to configure server SSL without being explicit about
whether to enable that configuration.
Backport of: #45892
* [ML] ML Model Inference Ingest Processor (#49052)
* [ML][Inference] adds lazy model loader and inference (#47410)
This adds a couple of things:
- A model loader service that is accessible via transport calls. This service will load in models and cache them. They will stay loaded until a processor no longer references them
- A Model class and its first sub-class LocalModel. Used to cache model information and run inference.
- Transport action and handler for requests to infer against a local model
Related Feature PRs:
* [ML][Inference] Adjust inference configuration option API (#47812)
* [ML][Inference] adds logistic_regression output aggregator (#48075)
* [ML][Inference] Adding read/del trained models (#47882)
* [ML][Inference] Adding inference ingest processor (#47859)
* [ML][Inference] fixing classification inference for ensemble (#48463)
* [ML][Inference] Adding model memory estimations (#48323)
* [ML][Inference] adding more options to inference processor (#48545)
* [ML][Inference] handle string values better in feature extraction (#48584)
* [ML][Inference] Adding _stats endpoint for inference (#48492)
* [ML][Inference] add inference processors and trained models to usage (#47869)
* [ML][Inference] add new flag for optionally including model definition (#48718)
* [ML][Inference] adding license checks (#49056)
* [ML][Inference] Adding memory and compute estimates to inference (#48955)
* fixing version of indexed docs for model inference
Backport of #48849. Update `.editorconfig` to make the Java settings the
default for all files, and then apply a 2-space indent to all `*.gradle`
files. Then reformat all the files.
* [ML] Add new geo_results.(actual_point|typical_point) fields for `lat_long` results (#47050)
[ML] Add new geo_results.(actual_point|typical_point) fields for `lat_long` results (#47050)
Related PR: https://github.com/elastic/ml-cpp/pull/809
* adjusting bwc version
This commit finishes cleaning up the AbstractHlrcXContentTestCase work
and removes this class. All classes that were using this are now using
the updated base class.
Ref #39745
The old graph tests were duplicated a lot and used a deprecated parent
class. This commit cleans that up and removes one of the duplicated
tests.
Ref #39745
* [ML][Inference] separating definition and config object storage (#48651)
This separates out the `definition` object from being stored within the configuration object in the index.
This allows us to gather the config object without decompressing a potentially large definition.
Additionally, `input` is moved to the TrainedModelConfig object and out of the definition. This is so the trained input fields are accessible outside the potentially large model definition.
Adding support for the `search_type` request parameter to the Ranking Evaluation
API since this parameter can impact the ranking and the metric score and should
be choosen in the same way when evaluating the search as later in the real
search.
Closes#48503
Backport of #48447. Make a number of changes so that code in the
`client` directory is more resilient to automatic formatting. This
covers:
* Literal JSON handling:
* Reformatting multiline JSON to embed whitespace in the strings
* Remove string concatenation where JSON fits on a single line
* Use `String.format` for large documents with variable content
* Remove some erroneous doc refs in `QueryDSLDocumentationTests`
* Move some comments around to they aren't auto-formatted to a strange
place
This commit simplifies and standardizes our usage of the Gradle Shadow
plugin to conform more to plugin conventions. The custom "bundle" plugin
has been removed as it's not necessary and performs the same function
as the Shadow plugin's default behavior with existing configurations.
Additionally, this removes unnecessary creation of a "nodeps" artifact,
which is unnecessary because by default project dependencies will in
fact use the non-shadowed JAR unless explicitly depending on the
"shadow" configuration.
Finally, we've cleaned up the logic used for unit testing, so we are
now correctly testing against the shadow JAR when the plugin is applied.
This better represents a real-world scenario for consumers and provides
better test coverage for incorrectly declared dependencies.
(cherry picked from commit 3698131109c7e78bdd3a3340707e1c7b4740d310)
Due to a bug, GETing a snapshot can cause a RespositoryException to be
thrown. This error is transient and should be retried, rather than
causing the test to fail. This commit converts those
RepositoryExceptions into AssertionErrors so that they will be retried
in code wrapped in assertBusy.
BytesReference is currently an abstract class which is extended by
various implementations. This makes it very difficult to use the
delegation pattern. The implication of this is that our releasable
BytesReference is a PagedBytesReference type and cannot be used as a
generic releasable bytes reference that delegates to any reference type.
This commit makes BytesReference an interface and introduces an
AbstractBytesReference for common functionality.
The AbstractHlrcWriteableXContentTestCase was replaced by a better test
case a while ago, and this is the last two instances using it. They have
been converted and the test is now deleted.
Ref #39745
This commit removes the randomization used by every execute call in the
high level rest tests. Previously every execute call, which can be many
calls per single test, would rely on a random boolean to determine if
they should use the sync or async methods provided to the execute
method. This commit runs the tests twice, using two different clusters,
both of them providing the value one time via a sysprop. This ensures
that the whole suite of tests is run using the sync and async code
paths.
Closes#39667
All internal searches (triggered by APIs) across the .security index
must be performed while "under the security origin". Otherwise,
the search is performed in the context of the caller which most
likely does not have privileges to search .security (hopefully).
This commit fixes this in the case of two methods in the
TokenService and corrects an overly done such context switch
in the ApiKeyService.
In addition, this makes all tests from the client/rest-high-level
module execute as an all mighty administrator,
but not a literal superuser.
Closes#47151
Several links from the ILM HLRC Javadoc to the online documentation were
not updated when the ILM HLRC documentation was written. This commit
fixes those links.
Adds `GET /_script_context`, returning a `contexts` object with each
available context as a key whose value is an empty object. eg.
```
{
"contexts": {
"aggregation_selector": {},
"aggs": {},
"aggs_combine": {},
...
}
}
```
refs: #47411
This adds parsing an inference model as a possible
result of the analytics process. When we do parse such a model
we persist a `TrainedModelConfig` into the inference index
that contains additional metadata derived from the running job.
which is backport merge and adds a new ingest processor, named enrich processor,
that allows document being ingested to be enriched with data from other indices.
Besides a new enrich processor, this PR adds several APIs to manage an enrich policy.
An enrich policy is in charge of making the data from other indices available to the enrich processor in an efficient manner.
Related to #32789
This change adds:
- A new option, allow_lazy_open, to anomaly detection jobs
- A new option, allow_lazy_start, to data frame analytics jobs
Both work in the same way: they allow a job to be
opened/started even if no ML node exists that can
accommodate the job immediately. In this situation
the job waits in the opening/starting state until ML
node capacity is available. (The starting state for data
frame analytics jobs is new in this change.)
Additionally, the ML nightly maintenance tasks now
creates audit warnings for ML jobs that are unassigned.
This means that jobs that cannot be assigned to an ML
node for a very long time will show a yellow warning
triangle in the UI.
A final change is that it is now possible to close a job
that is not assigned to a node without using force.
This is because previously jobs that were open but
not assigned to a node were an aberration, whereas
after this change they'll be relatively common.
This commit adds HLRC support and documentation for the SLM Start and
Stop APIs, as well as updating existing documentation where appropriate.
This commit also ensures that the SLM APIs are properly included in the
HLRC documentation.
Elastic cloud has a concept of a cloud Id. This Id is a base64 encoded
url, split up into a few parts. This commit allows the user to pass in a
cloud id now, which is translated to a HttpHost that is defined by the
encoded parts therein.
Adds a new datafeed config option, max_empty_searches,
that tells a datafeed that has never found any data to stop
itself and close its associated job after a certain number
of real-time searches have returned no data.
Backport of #47922
Tim Vernum
Benjamin Trent
Przemysław Witek
Dimitris Athanasiou
Rory Hunter
Alan Woodward
Michael Basnight
Dan Hermann
Gordon Brown
Christoph Büscher
Mark Vieira
David Turner
Tanguy Leroux
Tim Brooks
Martijn van Groningen
Lee Hinman
Albert Zaharovits
Stuart Tettemer
David Roberts