Viewing docs for elasticstack 0.16.3
published on Thursday, Jul 23, 2026 by elastic
published on Thursday, Jul 23, 2026 by elastic
Viewing docs for elasticstack 0.16.3
published on Thursday, Jul 23, 2026 by elastic
published on Thursday, Jul 23, 2026 by elastic
Retrieves an Elasticsearch ML trained model. See, https://www.elastic.co/guide/en/elasticsearch/reference/current/get-trained-models.html
Example Usage
import * as pulumi from "@pulumi/pulumi";
import * as elasticstack from "@pulumi/elasticstack";
const example = elasticstack.getElasticsearchMlTrainedModel({
modelId: "lang_ident_model_current",
});
import pulumi
import pulumi_elasticstack as elasticstack
example = elasticstack.get_elasticsearch_ml_trained_model(model_id="lang_ident_model_current")
package main
import (
"github.com/pulumi/pulumi-terraform-provider/sdks/go/elasticstack/elasticstack"
"github.com/pulumi/pulumi/sdk/v3/go/pulumi"
)
func main() {
pulumi.Run(func(ctx *pulumi.Context) error {
_, err := elasticstack.GetElasticsearchMlTrainedModel(ctx, &elasticstack.GetElasticsearchMlTrainedModelArgs{
ModelId: "lang_ident_model_current",
}, nil)
if err != nil {
return err
}
return nil
})
}
using System.Collections.Generic;
using System.Linq;
using Pulumi;
using Elasticstack = Pulumi.Elasticstack;
return await Deployment.RunAsync(() =>
{
var example = Elasticstack.GetElasticsearchMlTrainedModel.Invoke(new()
{
ModelId = "lang_ident_model_current",
});
});
package generated_program;
import com.pulumi.Context;
import com.pulumi.Pulumi;
import com.pulumi.core.Output;
import com.pulumi.elasticstack.ElasticstackFunctions;
import com.pulumi.elasticstack.inputs.GetElasticsearchMlTrainedModelArgs;
import java.util.List;
import java.util.ArrayList;
import java.util.Map;
import java.io.File;
import java.nio.file.Files;
import java.nio.file.Paths;
public class App {
public static void main(String[] args) {
Pulumi.run(App::stack);
}
public static void stack(Context ctx) {
final var example = ElasticstackFunctions.getElasticsearchMlTrainedModel(GetElasticsearchMlTrainedModelArgs.builder()
.modelId("lang_ident_model_current")
.build());
}
}
variables:
example:
fn::invoke:
function: elasticstack:getElasticsearchMlTrainedModel
arguments:
modelId: lang_ident_model_current
Example coming soon!
Using getElasticsearchMlTrainedModel
Two invocation forms are available. The direct form accepts plain arguments and either blocks until the result value is available, or returns a Promise-wrapped result. The output form accepts Input-wrapped arguments and returns an Output-wrapped result.
function getElasticsearchMlTrainedModel(args: GetElasticsearchMlTrainedModelArgs, opts?: InvokeOptions): Promise<GetElasticsearchMlTrainedModelResult>
function getElasticsearchMlTrainedModelOutput(args: GetElasticsearchMlTrainedModelOutputArgs, opts?: InvokeOptions): Output<GetElasticsearchMlTrainedModelResult>def get_elasticsearch_ml_trained_model(elasticsearch_connections: Optional[Sequence[GetElasticsearchMlTrainedModelElasticsearchConnection]] = None,
model_id: Optional[str] = None,
opts: Optional[InvokeOptions] = None) -> GetElasticsearchMlTrainedModelResult
def get_elasticsearch_ml_trained_model_output(elasticsearch_connections: pulumi.Input[Optional[Sequence[pulumi.Input[GetElasticsearchMlTrainedModelElasticsearchConnectionArgs]]]] = None,
model_id: pulumi.Input[Optional[str]] = None,
opts: Optional[InvokeOptions] = None) -> Output[GetElasticsearchMlTrainedModelResult]func GetElasticsearchMlTrainedModel(ctx *Context, args *GetElasticsearchMlTrainedModelArgs, opts ...InvokeOption) (*GetElasticsearchMlTrainedModelResult, error)
func GetElasticsearchMlTrainedModelOutput(ctx *Context, args *GetElasticsearchMlTrainedModelOutputArgs, opts ...InvokeOption) GetElasticsearchMlTrainedModelResultOutput> Note: This function is named GetElasticsearchMlTrainedModel in the Go SDK.
public static class GetElasticsearchMlTrainedModel
{
public static Task<GetElasticsearchMlTrainedModelResult> InvokeAsync(GetElasticsearchMlTrainedModelArgs args, InvokeOptions? opts = null)
public static Output<GetElasticsearchMlTrainedModelResult> Invoke(GetElasticsearchMlTrainedModelInvokeArgs args, InvokeOptions? opts = null)
}public static CompletableFuture<GetElasticsearchMlTrainedModelResult> getElasticsearchMlTrainedModel(GetElasticsearchMlTrainedModelArgs args, InvokeOptions options)
public static Output<GetElasticsearchMlTrainedModelResult> getElasticsearchMlTrainedModel(GetElasticsearchMlTrainedModelArgs args, InvokeOptions options)
fn::invoke:
function: elasticstack:index/getElasticsearchMlTrainedModel:getElasticsearchMlTrainedModel
arguments:
# arguments dictionarydata "elasticstack_get_elasticsearch_ml_trained_model" "name" {
# arguments
}The following arguments are supported:
- Model
Id string - The identifier for the trained model.
- Elasticsearch
Connections List<GetElasticsearch Ml Trained Model Elasticsearch Connection> - Elasticsearch connection configuration block.
- Model
Id string - The identifier for the trained model.
- Elasticsearch
Connections []GetElasticsearch Ml Trained Model Elasticsearch Connection - Elasticsearch connection configuration block.
- model_
id string - The identifier for the trained model.
- elasticsearch_
connections list(object) - Elasticsearch connection configuration block.
- model
Id String - The identifier for the trained model.
- elasticsearch
Connections List<GetElasticsearch Ml Trained Model Elasticsearch Connection> - Elasticsearch connection configuration block.
- model
Id string - The identifier for the trained model.
- elasticsearch
Connections GetElasticsearch Ml Trained Model Elasticsearch Connection[] - Elasticsearch connection configuration block.
- model_
id str - The identifier for the trained model.
- elasticsearch_
connections Sequence[GetElasticsearch Ml Trained Model Elasticsearch Connection] - Elasticsearch connection configuration block.
- model
Id String - The identifier for the trained model.
- elasticsearch
Connections List<Property Map> - Elasticsearch connection configuration block.
getElasticsearchMlTrainedModel Result
The following output properties are available:
- Create
Time string - The time when the trained model was created.
- Created
By string - Information on the creator of the trained model.
- Default
Field Dictionary<string, string>Map - Any field map described in the inference configuration takes precedence.
- Description string
- The free-text description of the trained model.
- Fully
Defined bool - True if the full model definition is present.
- Id string
- Internal identifier of the resource
- Inference
Config stringJson - JSON string of the default inference configuration.
- Input
Json string - JSON string of the model input field names.
- License
Level string - The license level of the trained model.
- Metadata
Json string - JSON string of the model metadata.
- Model
Id string - The identifier for the trained model.
- Model
Size doubleBytes - The estimated memory usage in bytes to keep the trained model in memory.
- Model
Type string - The model type.
- Platform
Architecture string - The platform identifier (e.g. linux-x86_64).
- List<string>
- A set of tags for the trained model.
- Version string
- The Elasticsearch version number in which the trained model was created.
- Elasticsearch
Connections List<GetElasticsearch Ml Trained Model Elasticsearch Connection> - Elasticsearch connection configuration block.
- Create
Time string - The time when the trained model was created.
- Created
By string - Information on the creator of the trained model.
- Default
Field map[string]stringMap - Any field map described in the inference configuration takes precedence.
- Description string
- The free-text description of the trained model.
- Fully
Defined bool - True if the full model definition is present.
- Id string
- Internal identifier of the resource
- Inference
Config stringJson - JSON string of the default inference configuration.
- Input
Json string - JSON string of the model input field names.
- License
Level string - The license level of the trained model.
- Metadata
Json string - JSON string of the model metadata.
- Model
Id string - The identifier for the trained model.
- Model
Size float64Bytes - The estimated memory usage in bytes to keep the trained model in memory.
- Model
Type string - The model type.
- Platform
Architecture string - The platform identifier (e.g. linux-x86_64).
- []string
- A set of tags for the trained model.
- Version string
- The Elasticsearch version number in which the trained model was created.
- Elasticsearch
Connections []GetElasticsearch Ml Trained Model Elasticsearch Connection - Elasticsearch connection configuration block.
- create_
time string - The time when the trained model was created.
- created_
by string - Information on the creator of the trained model.
- default_
field_ map(string)map - Any field map described in the inference configuration takes precedence.
- description string
- The free-text description of the trained model.
- fully_
defined bool - True if the full model definition is present.
- id string
- Internal identifier of the resource
- inference_
config_ stringjson - JSON string of the default inference configuration.
- input_
json string - JSON string of the model input field names.
- license_
level string - The license level of the trained model.
- metadata_
json string - JSON string of the model metadata.
- model_
id string - The identifier for the trained model.
- model_
size_ numberbytes - The estimated memory usage in bytes to keep the trained model in memory.
- model_
type string - The model type.
- platform_
architecture string - The platform identifier (e.g. linux-x86_64).
- list(string)
- A set of tags for the trained model.
- version string
- The Elasticsearch version number in which the trained model was created.
- elasticsearch_
connections list(object) - Elasticsearch connection configuration block.
- create
Time String - The time when the trained model was created.
- created
By String - Information on the creator of the trained model.
- default
Field Map<String,String>Map - Any field map described in the inference configuration takes precedence.
- description String
- The free-text description of the trained model.
- fully
Defined Boolean - True if the full model definition is present.
- id String
- Internal identifier of the resource
- inference
Config StringJson - JSON string of the default inference configuration.
- input
Json String - JSON string of the model input field names.
- license
Level String - The license level of the trained model.
- metadata
Json String - JSON string of the model metadata.
- model
Id String - The identifier for the trained model.
- model
Size DoubleBytes - The estimated memory usage in bytes to keep the trained model in memory.
- model
Type String - The model type.
- platform
Architecture String - The platform identifier (e.g. linux-x86_64).
- List<String>
- A set of tags for the trained model.
- version String
- The Elasticsearch version number in which the trained model was created.
- elasticsearch
Connections List<GetElasticsearch Ml Trained Model Elasticsearch Connection> - Elasticsearch connection configuration block.
- create
Time string - The time when the trained model was created.
- created
By string - Information on the creator of the trained model.
- default
Field {[key: string]: string}Map - Any field map described in the inference configuration takes precedence.
- description string
- The free-text description of the trained model.
- fully
Defined boolean - True if the full model definition is present.
- id string
- Internal identifier of the resource
- inference
Config stringJson - JSON string of the default inference configuration.
- input
Json string - JSON string of the model input field names.
- license
Level string - The license level of the trained model.
- metadata
Json string - JSON string of the model metadata.
- model
Id string - The identifier for the trained model.
- model
Size numberBytes - The estimated memory usage in bytes to keep the trained model in memory.
- model
Type string - The model type.
- platform
Architecture string - The platform identifier (e.g. linux-x86_64).
- string[]
- A set of tags for the trained model.
- version string
- The Elasticsearch version number in which the trained model was created.
- elasticsearch
Connections GetElasticsearch Ml Trained Model Elasticsearch Connection[] - Elasticsearch connection configuration block.
- create_
time str - The time when the trained model was created.
- created_
by str - Information on the creator of the trained model.
- default_
field_ Mapping[str, str]map - Any field map described in the inference configuration takes precedence.
- description str
- The free-text description of the trained model.
- fully_
defined bool - True if the full model definition is present.
- id str
- Internal identifier of the resource
- inference_
config_ strjson - JSON string of the default inference configuration.
- input_
json str - JSON string of the model input field names.
- license_
level str - The license level of the trained model.
- metadata_
json str - JSON string of the model metadata.
- model_
id str - The identifier for the trained model.
- model_
size_ floatbytes - The estimated memory usage in bytes to keep the trained model in memory.
- model_
type str - The model type.
- platform_
architecture str - The platform identifier (e.g. linux-x86_64).
- Sequence[str]
- A set of tags for the trained model.
- version str
- The Elasticsearch version number in which the trained model was created.
- elasticsearch_
connections Sequence[GetElasticsearch Ml Trained Model Elasticsearch Connection] - Elasticsearch connection configuration block.
- create
Time String - The time when the trained model was created.
- created
By String - Information on the creator of the trained model.
- default
Field Map<String>Map - Any field map described in the inference configuration takes precedence.
- description String
- The free-text description of the trained model.
- fully
Defined Boolean - True if the full model definition is present.
- id String
- Internal identifier of the resource
- inference
Config StringJson - JSON string of the default inference configuration.
- input
Json String - JSON string of the model input field names.
- license
Level String - The license level of the trained model.
- metadata
Json String - JSON string of the model metadata.
- model
Id String - The identifier for the trained model.
- model
Size NumberBytes - The estimated memory usage in bytes to keep the trained model in memory.
- model
Type String - The model type.
- platform
Architecture String - The platform identifier (e.g. linux-x86_64).
- List<String>
- A set of tags for the trained model.
- version String
- The Elasticsearch version number in which the trained model was created.
- elasticsearch
Connections List<Property Map> - Elasticsearch connection configuration block.
Supporting Types
GetElasticsearchMlTrainedModelElasticsearchConnection
- Api
Key string - API Key to use for authentication to Elasticsearch
- Bearer
Token string - Bearer Token to use for authentication to Elasticsearch
- Ca
Data string - PEM-encoded custom Certificate Authority certificate
- Ca
File string - Path to a custom Certificate Authority certificate
- Ca
Fingerprint string - SHA-256 hex fingerprint (64 hexadecimal characters, no colons or separators) of the server TLS certificate used to pin the connection instead of a full CA chain
- Cert
Data string - PEM encoded certificate for client auth
- Cert
File string - Path to a file containing the PEM encoded certificate for client auth
- Endpoints List<string>
- Es
Client stringAuthentication - ES Client Authentication field to be used with the JWT token
- Headers Dictionary<string, string>
- A list of headers to be sent with each request to Elasticsearch.
- Insecure bool
- Disable TLS certificate validation
- Key
Data string - PEM encoded private key for client auth
- Key
File string - Path to a file containing the PEM encoded private key for client auth
- Password string
- Password to use for API authentication to Elasticsearch.
- Username string
- Username to use for API authentication to Elasticsearch.
- Api
Key string - API Key to use for authentication to Elasticsearch
- Bearer
Token string - Bearer Token to use for authentication to Elasticsearch
- Ca
Data string - PEM-encoded custom Certificate Authority certificate
- Ca
File string - Path to a custom Certificate Authority certificate
- Ca
Fingerprint string - SHA-256 hex fingerprint (64 hexadecimal characters, no colons or separators) of the server TLS certificate used to pin the connection instead of a full CA chain
- Cert
Data string - PEM encoded certificate for client auth
- Cert
File string - Path to a file containing the PEM encoded certificate for client auth
- Endpoints []string
- Es
Client stringAuthentication - ES Client Authentication field to be used with the JWT token
- Headers map[string]string
- A list of headers to be sent with each request to Elasticsearch.
- Insecure bool
- Disable TLS certificate validation
- Key
Data string - PEM encoded private key for client auth
- Key
File string - Path to a file containing the PEM encoded private key for client auth
- Password string
- Password to use for API authentication to Elasticsearch.
- Username string
- Username to use for API authentication to Elasticsearch.
- api_
key string - API Key to use for authentication to Elasticsearch
- bearer_
token string - Bearer Token to use for authentication to Elasticsearch
- ca_
data string - PEM-encoded custom Certificate Authority certificate
- ca_
file string - Path to a custom Certificate Authority certificate
- ca_
fingerprint string - SHA-256 hex fingerprint (64 hexadecimal characters, no colons or separators) of the server TLS certificate used to pin the connection instead of a full CA chain
- cert_
data string - PEM encoded certificate for client auth
- cert_
file string - Path to a file containing the PEM encoded certificate for client auth
- endpoints list(string)
- es_
client_ stringauthentication - ES Client Authentication field to be used with the JWT token
- headers map(string)
- A list of headers to be sent with each request to Elasticsearch.
- insecure bool
- Disable TLS certificate validation
- key_
data string - PEM encoded private key for client auth
- key_
file string - Path to a file containing the PEM encoded private key for client auth
- password string
- Password to use for API authentication to Elasticsearch.
- username string
- Username to use for API authentication to Elasticsearch.
- api
Key String - API Key to use for authentication to Elasticsearch
- bearer
Token String - Bearer Token to use for authentication to Elasticsearch
- ca
Data String - PEM-encoded custom Certificate Authority certificate
- ca
File String - Path to a custom Certificate Authority certificate
- ca
Fingerprint String - SHA-256 hex fingerprint (64 hexadecimal characters, no colons or separators) of the server TLS certificate used to pin the connection instead of a full CA chain
- cert
Data String - PEM encoded certificate for client auth
- cert
File String - Path to a file containing the PEM encoded certificate for client auth
- endpoints List<String>
- es
Client StringAuthentication - ES Client Authentication field to be used with the JWT token
- headers Map<String,String>
- A list of headers to be sent with each request to Elasticsearch.
- insecure Boolean
- Disable TLS certificate validation
- key
Data String - PEM encoded private key for client auth
- key
File String - Path to a file containing the PEM encoded private key for client auth
- password String
- Password to use for API authentication to Elasticsearch.
- username String
- Username to use for API authentication to Elasticsearch.
- api
Key string - API Key to use for authentication to Elasticsearch
- bearer
Token string - Bearer Token to use for authentication to Elasticsearch
- ca
Data string - PEM-encoded custom Certificate Authority certificate
- ca
File string - Path to a custom Certificate Authority certificate
- ca
Fingerprint string - SHA-256 hex fingerprint (64 hexadecimal characters, no colons or separators) of the server TLS certificate used to pin the connection instead of a full CA chain
- cert
Data string - PEM encoded certificate for client auth
- cert
File string - Path to a file containing the PEM encoded certificate for client auth
- endpoints string[]
- es
Client stringAuthentication - ES Client Authentication field to be used with the JWT token
- headers {[key: string]: string}
- A list of headers to be sent with each request to Elasticsearch.
- insecure boolean
- Disable TLS certificate validation
- key
Data string - PEM encoded private key for client auth
- key
File string - Path to a file containing the PEM encoded private key for client auth
- password string
- Password to use for API authentication to Elasticsearch.
- username string
- Username to use for API authentication to Elasticsearch.
- api_
key str - API Key to use for authentication to Elasticsearch
- bearer_
token str - Bearer Token to use for authentication to Elasticsearch
- ca_
data str - PEM-encoded custom Certificate Authority certificate
- ca_
file str - Path to a custom Certificate Authority certificate
- ca_
fingerprint str - SHA-256 hex fingerprint (64 hexadecimal characters, no colons or separators) of the server TLS certificate used to pin the connection instead of a full CA chain
- cert_
data str - PEM encoded certificate for client auth
- cert_
file str - Path to a file containing the PEM encoded certificate for client auth
- endpoints Sequence[str]
- es_
client_ strauthentication - ES Client Authentication field to be used with the JWT token
- headers Mapping[str, str]
- A list of headers to be sent with each request to Elasticsearch.
- insecure bool
- Disable TLS certificate validation
- key_
data str - PEM encoded private key for client auth
- key_
file str - Path to a file containing the PEM encoded private key for client auth
- password str
- Password to use for API authentication to Elasticsearch.
- username str
- Username to use for API authentication to Elasticsearch.
- api
Key String - API Key to use for authentication to Elasticsearch
- bearer
Token String - Bearer Token to use for authentication to Elasticsearch
- ca
Data String - PEM-encoded custom Certificate Authority certificate
- ca
File String - Path to a custom Certificate Authority certificate
- ca
Fingerprint String - SHA-256 hex fingerprint (64 hexadecimal characters, no colons or separators) of the server TLS certificate used to pin the connection instead of a full CA chain
- cert
Data String - PEM encoded certificate for client auth
- cert
File String - Path to a file containing the PEM encoded certificate for client auth
- endpoints List<String>
- es
Client StringAuthentication - ES Client Authentication field to be used with the JWT token
- headers Map<String>
- A list of headers to be sent with each request to Elasticsearch.
- insecure Boolean
- Disable TLS certificate validation
- key
Data String - PEM encoded private key for client auth
- key
File String - Path to a file containing the PEM encoded private key for client auth
- password String
- Password to use for API authentication to Elasticsearch.
- username String
- Username to use for API authentication to Elasticsearch.
Package Details
- Repository
- elasticstack elastic/terraform-provider-elasticstack
- License
- Notes
- This Pulumi package is based on the
elasticstackTerraform Provider.
Viewing docs for elasticstack 0.16.3
published on Thursday, Jul 23, 2026 by elastic
published on Thursday, Jul 23, 2026 by elastic