Viewing docs for elasticstack 0.15.0
published on Thursday, May 14, 2026 by elastic
published on Thursday, May 14, 2026 by elastic
Viewing docs for elasticstack 0.15.0
published on Thursday, May 14, 2026 by elastic
published on Thursday, May 14, 2026 by elastic
Creates or updates an inference endpoint.See the inference endpoint API documentation for more details.
Example Usage
import * as pulumi from "@pulumi/pulumi";
import * as elasticstack from "@pulumi/elasticstack";
const example = new elasticstack.ElasticsearchInferenceEndpoint("example", {
inferenceId: "text-embedding-3-large",
taskType: "text_embedding",
service: "azureaistudio",
serviceSettings: JSON.stringify({
api_key: "example_key",
target: "https://example.com/openai/deployments/text-embedding-3-large/embeddings?api-version=2023-05-151",
provider: "openai",
endpoint_type: "token",
}),
});
import pulumi
import json
import pulumi_elasticstack as elasticstack
example = elasticstack.ElasticsearchInferenceEndpoint("example",
inference_id="text-embedding-3-large",
task_type="text_embedding",
service="azureaistudio",
service_settings=json.dumps({
"api_key": "example_key",
"target": "https://example.com/openai/deployments/text-embedding-3-large/embeddings?api-version=2023-05-151",
"provider": "openai",
"endpoint_type": "token",
}))
package main
import (
"encoding/json"
"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 {
tmpJSON0, err := json.Marshal(map[string]interface{}{
"api_key": "example_key",
"target": "https://example.com/openai/deployments/text-embedding-3-large/embeddings?api-version=2023-05-151",
"provider": "openai",
"endpoint_type": "token",
})
if err != nil {
return err
}
json0 := string(tmpJSON0)
_, err = elasticstack.NewElasticsearchInferenceEndpoint(ctx, "example", &elasticstack.ElasticsearchInferenceEndpointArgs{
InferenceId: pulumi.String("text-embedding-3-large"),
TaskType: pulumi.String("text_embedding"),
Service: pulumi.String("azureaistudio"),
ServiceSettings: pulumi.String(json0),
})
if err != nil {
return err
}
return nil
})
}
using System.Collections.Generic;
using System.Linq;
using System.Text.Json;
using Pulumi;
using Elasticstack = Pulumi.Elasticstack;
return await Deployment.RunAsync(() =>
{
var example = new Elasticstack.ElasticsearchInferenceEndpoint("example", new()
{
InferenceId = "text-embedding-3-large",
TaskType = "text_embedding",
Service = "azureaistudio",
ServiceSettings = JsonSerializer.Serialize(new Dictionary<string, object?>
{
["api_key"] = "example_key",
["target"] = "https://example.com/openai/deployments/text-embedding-3-large/embeddings?api-version=2023-05-151",
["provider"] = "openai",
["endpoint_type"] = "token",
}),
});
});
package generated_program;
import com.pulumi.Context;
import com.pulumi.Pulumi;
import com.pulumi.core.Output;
import com.pulumi.elasticstack.ElasticsearchInferenceEndpoint;
import com.pulumi.elasticstack.ElasticsearchInferenceEndpointArgs;
import static com.pulumi.codegen.internal.Serialization.*;
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) {
var example = new ElasticsearchInferenceEndpoint("example", ElasticsearchInferenceEndpointArgs.builder()
.inferenceId("text-embedding-3-large")
.taskType("text_embedding")
.service("azureaistudio")
.serviceSettings(serializeJson(
jsonObject(
jsonProperty("api_key", "example_key"),
jsonProperty("target", "https://example.com/openai/deployments/text-embedding-3-large/embeddings?api-version=2023-05-151"),
jsonProperty("provider", "openai"),
jsonProperty("endpoint_type", "token")
)))
.build());
}
}
resources:
example:
type: elasticstack:ElasticsearchInferenceEndpoint
properties:
inferenceId: text-embedding-3-large
taskType: text_embedding
service: azureaistudio
serviceSettings:
fn::toJSON:
api_key: example_key
target: https://example.com/openai/deployments/text-embedding-3-large/embeddings?api-version=2023-05-151
provider: openai
endpoint_type: token
Example coming soon!
Create ElasticsearchInferenceEndpoint Resource
Resources are created with functions called constructors. To learn more about declaring and configuring resources, see Resources.
Constructor syntax
new ElasticsearchInferenceEndpoint(name: string, args: ElasticsearchInferenceEndpointArgs, opts?: CustomResourceOptions);@overload
def ElasticsearchInferenceEndpoint(resource_name: str,
args: ElasticsearchInferenceEndpointArgs,
opts: Optional[ResourceOptions] = None)
@overload
def ElasticsearchInferenceEndpoint(resource_name: str,
opts: Optional[ResourceOptions] = None,
inference_id: Optional[str] = None,
service: Optional[str] = None,
service_settings: Optional[str] = None,
chunking_settings: Optional[str] = None,
elasticsearch_connections: Optional[Sequence[ElasticsearchInferenceEndpointElasticsearchConnectionArgs]] = None,
task_settings: Optional[str] = None,
task_type: Optional[str] = None)func NewElasticsearchInferenceEndpoint(ctx *Context, name string, args ElasticsearchInferenceEndpointArgs, opts ...ResourceOption) (*ElasticsearchInferenceEndpoint, error)public ElasticsearchInferenceEndpoint(string name, ElasticsearchInferenceEndpointArgs args, CustomResourceOptions? opts = null)
public ElasticsearchInferenceEndpoint(String name, ElasticsearchInferenceEndpointArgs args)
public ElasticsearchInferenceEndpoint(String name, ElasticsearchInferenceEndpointArgs args, CustomResourceOptions options)
type: elasticstack:ElasticsearchInferenceEndpoint
properties: # The arguments to resource properties.
options: # Bag of options to control resource's behavior.
resource "elasticstack_elasticsearchinferenceendpoint" "name" {
# resource properties
}Parameters
- name string
- The unique name of the resource.
- args ElasticsearchInferenceEndpointArgs
- The arguments to resource properties.
- opts CustomResourceOptions
- Bag of options to control resource's behavior.
- resource_name str
- The unique name of the resource.
- args ElasticsearchInferenceEndpointArgs
- The arguments to resource properties.
- opts ResourceOptions
- Bag of options to control resource's behavior.
- ctx Context
- Context object for the current deployment.
- name string
- The unique name of the resource.
- args ElasticsearchInferenceEndpointArgs
- The arguments to resource properties.
- opts ResourceOption
- Bag of options to control resource's behavior.
- name string
- The unique name of the resource.
- args ElasticsearchInferenceEndpointArgs
- The arguments to resource properties.
- opts CustomResourceOptions
- Bag of options to control resource's behavior.
- name String
- The unique name of the resource.
- args ElasticsearchInferenceEndpointArgs
- The arguments to resource properties.
- options CustomResourceOptions
- Bag of options to control resource's behavior.
Constructor example
The following reference example uses placeholder values for all input properties.
var elasticsearchInferenceEndpointResource = new Elasticstack.ElasticsearchInferenceEndpoint("elasticsearchInferenceEndpointResource", new()
{
InferenceId = "string",
Service = "string",
ServiceSettings = "string",
ChunkingSettings = "string",
ElasticsearchConnections = new[]
{
new Elasticstack.Inputs.ElasticsearchInferenceEndpointElasticsearchConnectionArgs
{
ApiKey = "string",
BearerToken = "string",
CaData = "string",
CaFile = "string",
CertData = "string",
CertFile = "string",
Endpoints = new[]
{
"string",
},
EsClientAuthentication = "string",
Headers =
{
{ "string", "string" },
},
Insecure = false,
KeyData = "string",
KeyFile = "string",
Password = "string",
Username = "string",
},
},
TaskSettings = "string",
TaskType = "string",
});
example, err := elasticstack.NewElasticsearchInferenceEndpoint(ctx, "elasticsearchInferenceEndpointResource", &elasticstack.ElasticsearchInferenceEndpointArgs{
InferenceId: pulumi.String("string"),
Service: pulumi.String("string"),
ServiceSettings: pulumi.String("string"),
ChunkingSettings: pulumi.String("string"),
ElasticsearchConnections: elasticstack.ElasticsearchInferenceEndpointElasticsearchConnectionArray{
&elasticstack.ElasticsearchInferenceEndpointElasticsearchConnectionArgs{
ApiKey: pulumi.String("string"),
BearerToken: pulumi.String("string"),
CaData: pulumi.String("string"),
CaFile: pulumi.String("string"),
CertData: pulumi.String("string"),
CertFile: pulumi.String("string"),
Endpoints: pulumi.StringArray{
pulumi.String("string"),
},
EsClientAuthentication: pulumi.String("string"),
Headers: pulumi.StringMap{
"string": pulumi.String("string"),
},
Insecure: pulumi.Bool(false),
KeyData: pulumi.String("string"),
KeyFile: pulumi.String("string"),
Password: pulumi.String("string"),
Username: pulumi.String("string"),
},
},
TaskSettings: pulumi.String("string"),
TaskType: pulumi.String("string"),
})
resource "elasticstack_elasticsearchinferenceendpoint" "elasticsearchInferenceEndpointResource" {
inference_id = "string"
service = "string"
service_settings = "string"
chunking_settings = "string"
elasticsearch_connections {
api_key = "string"
bearer_token = "string"
ca_data = "string"
ca_file = "string"
cert_data = "string"
cert_file = "string"
endpoints = ["string"]
es_client_authentication = "string"
headers = {
"string" = "string"
}
insecure = false
key_data = "string"
key_file = "string"
password = "string"
username = "string"
}
task_settings = "string"
task_type = "string"
}
var elasticsearchInferenceEndpointResource = new ElasticsearchInferenceEndpoint("elasticsearchInferenceEndpointResource", ElasticsearchInferenceEndpointArgs.builder()
.inferenceId("string")
.service("string")
.serviceSettings("string")
.chunkingSettings("string")
.elasticsearchConnections(ElasticsearchInferenceEndpointElasticsearchConnectionArgs.builder()
.apiKey("string")
.bearerToken("string")
.caData("string")
.caFile("string")
.certData("string")
.certFile("string")
.endpoints("string")
.esClientAuthentication("string")
.headers(Map.of("string", "string"))
.insecure(false)
.keyData("string")
.keyFile("string")
.password("string")
.username("string")
.build())
.taskSettings("string")
.taskType("string")
.build());
elasticsearch_inference_endpoint_resource = elasticstack.ElasticsearchInferenceEndpoint("elasticsearchInferenceEndpointResource",
inference_id="string",
service="string",
service_settings="string",
chunking_settings="string",
elasticsearch_connections=[{
"api_key": "string",
"bearer_token": "string",
"ca_data": "string",
"ca_file": "string",
"cert_data": "string",
"cert_file": "string",
"endpoints": ["string"],
"es_client_authentication": "string",
"headers": {
"string": "string",
},
"insecure": False,
"key_data": "string",
"key_file": "string",
"password": "string",
"username": "string",
}],
task_settings="string",
task_type="string")
const elasticsearchInferenceEndpointResource = new elasticstack.ElasticsearchInferenceEndpoint("elasticsearchInferenceEndpointResource", {
inferenceId: "string",
service: "string",
serviceSettings: "string",
chunkingSettings: "string",
elasticsearchConnections: [{
apiKey: "string",
bearerToken: "string",
caData: "string",
caFile: "string",
certData: "string",
certFile: "string",
endpoints: ["string"],
esClientAuthentication: "string",
headers: {
string: "string",
},
insecure: false,
keyData: "string",
keyFile: "string",
password: "string",
username: "string",
}],
taskSettings: "string",
taskType: "string",
});
type: elasticstack:ElasticsearchInferenceEndpoint
properties:
chunkingSettings: string
elasticsearchConnections:
- apiKey: string
bearerToken: string
caData: string
caFile: string
certData: string
certFile: string
endpoints:
- string
esClientAuthentication: string
headers:
string: string
insecure: false
keyData: string
keyFile: string
password: string
username: string
inferenceId: string
service: string
serviceSettings: string
taskSettings: string
taskType: string
ElasticsearchInferenceEndpoint Resource Properties
To learn more about resource properties and how to use them, see Inputs and Outputs in the Architecture and Concepts docs.
Inputs
In Python, inputs that are objects can be passed either as argument classes or as dictionary literals.
The ElasticsearchInferenceEndpoint resource accepts the following input properties:
- Inference
Id string - The unique identifier of the inference endpoint.
- Service string
- The service type for the inference endpoint (e.g.
openai,cohere,elasticsearch). - Service
Settings string - Settings specific to the service provider, as a JSON object. May include credentials and model identifiers.
- Chunking
Settings string - Configuration for chunking input text, as a JSON object. Applicable only for embedding task types.
- Elasticsearch
Connections List<ElasticsearchInference Endpoint Elasticsearch Connection> - Elasticsearch connection configuration block.
- Task
Settings string - Task-specific settings, as a JSON object. Optional and service-dependent. Only keys explicitly set here are tracked; server-applied defaults returned by the API are ignored to avoid perpetual drift.
- Task
Type string - must be one of [
sparse_embedding,text_embedding,rerank,completion,chat_completion,embedding]
- Inference
Id string - The unique identifier of the inference endpoint.
- Service string
- The service type for the inference endpoint (e.g.
openai,cohere,elasticsearch). - Service
Settings string - Settings specific to the service provider, as a JSON object. May include credentials and model identifiers.
- Chunking
Settings string - Configuration for chunking input text, as a JSON object. Applicable only for embedding task types.
- Elasticsearch
Connections []ElasticsearchInference Endpoint Elasticsearch Connection Args - Elasticsearch connection configuration block.
- Task
Settings string - Task-specific settings, as a JSON object. Optional and service-dependent. Only keys explicitly set here are tracked; server-applied defaults returned by the API are ignored to avoid perpetual drift.
- Task
Type string - must be one of [
sparse_embedding,text_embedding,rerank,completion,chat_completion,embedding]
- inference_
id string - The unique identifier of the inference endpoint.
- service string
- The service type for the inference endpoint (e.g.
openai,cohere,elasticsearch). - service_
settings string - Settings specific to the service provider, as a JSON object. May include credentials and model identifiers.
- chunking_
settings string - Configuration for chunking input text, as a JSON object. Applicable only for embedding task types.
- elasticsearch_
connections list(object) - Elasticsearch connection configuration block.
- task_
settings string - Task-specific settings, as a JSON object. Optional and service-dependent. Only keys explicitly set here are tracked; server-applied defaults returned by the API are ignored to avoid perpetual drift.
- task_
type string - must be one of [
sparse_embedding,text_embedding,rerank,completion,chat_completion,embedding]
- inference
Id String - The unique identifier of the inference endpoint.
- service String
- The service type for the inference endpoint (e.g.
openai,cohere,elasticsearch). - service
Settings String - Settings specific to the service provider, as a JSON object. May include credentials and model identifiers.
- chunking
Settings String - Configuration for chunking input text, as a JSON object. Applicable only for embedding task types.
- elasticsearch
Connections List<ElasticsearchInference Endpoint Elasticsearch Connection> - Elasticsearch connection configuration block.
- task
Settings String - Task-specific settings, as a JSON object. Optional and service-dependent. Only keys explicitly set here are tracked; server-applied defaults returned by the API are ignored to avoid perpetual drift.
- task
Type String - must be one of [
sparse_embedding,text_embedding,rerank,completion,chat_completion,embedding]
- inference
Id string - The unique identifier of the inference endpoint.
- service string
- The service type for the inference endpoint (e.g.
openai,cohere,elasticsearch). - service
Settings string - Settings specific to the service provider, as a JSON object. May include credentials and model identifiers.
- chunking
Settings string - Configuration for chunking input text, as a JSON object. Applicable only for embedding task types.
- elasticsearch
Connections ElasticsearchInference Endpoint Elasticsearch Connection[] - Elasticsearch connection configuration block.
- task
Settings string - Task-specific settings, as a JSON object. Optional and service-dependent. Only keys explicitly set here are tracked; server-applied defaults returned by the API are ignored to avoid perpetual drift.
- task
Type string - must be one of [
sparse_embedding,text_embedding,rerank,completion,chat_completion,embedding]
- inference_
id str - The unique identifier of the inference endpoint.
- service str
- The service type for the inference endpoint (e.g.
openai,cohere,elasticsearch). - service_
settings str - Settings specific to the service provider, as a JSON object. May include credentials and model identifiers.
- chunking_
settings str - Configuration for chunking input text, as a JSON object. Applicable only for embedding task types.
- elasticsearch_
connections Sequence[ElasticsearchInference Endpoint Elasticsearch Connection Args] - Elasticsearch connection configuration block.
- task_
settings str - Task-specific settings, as a JSON object. Optional and service-dependent. Only keys explicitly set here are tracked; server-applied defaults returned by the API are ignored to avoid perpetual drift.
- task_
type str - must be one of [
sparse_embedding,text_embedding,rerank,completion,chat_completion,embedding]
- inference
Id String - The unique identifier of the inference endpoint.
- service String
- The service type for the inference endpoint (e.g.
openai,cohere,elasticsearch). - service
Settings String - Settings specific to the service provider, as a JSON object. May include credentials and model identifiers.
- chunking
Settings String - Configuration for chunking input text, as a JSON object. Applicable only for embedding task types.
- elasticsearch
Connections List<Property Map> - Elasticsearch connection configuration block.
- task
Settings String - Task-specific settings, as a JSON object. Optional and service-dependent. Only keys explicitly set here are tracked; server-applied defaults returned by the API are ignored to avoid perpetual drift.
- task
Type String - must be one of [
sparse_embedding,text_embedding,rerank,completion,chat_completion,embedding]
Outputs
All input properties are implicitly available as output properties. Additionally, the ElasticsearchInferenceEndpoint resource produces the following output properties:
- Id string
- The provider-assigned unique ID for this managed resource.
- Id string
- The provider-assigned unique ID for this managed resource.
- id string
- The provider-assigned unique ID for this managed resource.
- id String
- The provider-assigned unique ID for this managed resource.
- id string
- The provider-assigned unique ID for this managed resource.
- id str
- The provider-assigned unique ID for this managed resource.
- id String
- The provider-assigned unique ID for this managed resource.
Look up Existing ElasticsearchInferenceEndpoint Resource
Get an existing ElasticsearchInferenceEndpoint resource’s state with the given name, ID, and optional extra properties used to qualify the lookup.
public static get(name: string, id: Input<ID>, state?: ElasticsearchInferenceEndpointState, opts?: CustomResourceOptions): ElasticsearchInferenceEndpoint@staticmethod
def get(resource_name: str,
id: str,
opts: Optional[ResourceOptions] = None,
chunking_settings: Optional[str] = None,
elasticsearch_connections: Optional[Sequence[ElasticsearchInferenceEndpointElasticsearchConnectionArgs]] = None,
inference_id: Optional[str] = None,
service: Optional[str] = None,
service_settings: Optional[str] = None,
task_settings: Optional[str] = None,
task_type: Optional[str] = None) -> ElasticsearchInferenceEndpointfunc GetElasticsearchInferenceEndpoint(ctx *Context, name string, id IDInput, state *ElasticsearchInferenceEndpointState, opts ...ResourceOption) (*ElasticsearchInferenceEndpoint, error)public static ElasticsearchInferenceEndpoint Get(string name, Input<string> id, ElasticsearchInferenceEndpointState? state, CustomResourceOptions? opts = null)public static ElasticsearchInferenceEndpoint get(String name, Output<String> id, ElasticsearchInferenceEndpointState state, CustomResourceOptions options)resources: _: type: elasticstack:ElasticsearchInferenceEndpoint get: id: ${id}import {
to = elasticstack_elasticsearchinferenceendpoint.example
id = "${id}"
}
- name
- The unique name of the resulting resource.
- id
- The unique provider ID of the resource to lookup.
- state
- Any extra arguments used during the lookup.
- opts
- A bag of options that control this resource's behavior.
- resource_name
- The unique name of the resulting resource.
- id
- The unique provider ID of the resource to lookup.
- name
- The unique name of the resulting resource.
- id
- The unique provider ID of the resource to lookup.
- state
- Any extra arguments used during the lookup.
- opts
- A bag of options that control this resource's behavior.
- name
- The unique name of the resulting resource.
- id
- The unique provider ID of the resource to lookup.
- state
- Any extra arguments used during the lookup.
- opts
- A bag of options that control this resource's behavior.
- name
- The unique name of the resulting resource.
- id
- The unique provider ID of the resource to lookup.
- state
- Any extra arguments used during the lookup.
- opts
- A bag of options that control this resource's behavior.
- Chunking
Settings string - Configuration for chunking input text, as a JSON object. Applicable only for embedding task types.
- Elasticsearch
Connections List<ElasticsearchInference Endpoint Elasticsearch Connection> - Elasticsearch connection configuration block.
- Inference
Id string - The unique identifier of the inference endpoint.
- Service string
- The service type for the inference endpoint (e.g.
openai,cohere,elasticsearch). - Service
Settings string - Settings specific to the service provider, as a JSON object. May include credentials and model identifiers.
- Task
Settings string - Task-specific settings, as a JSON object. Optional and service-dependent. Only keys explicitly set here are tracked; server-applied defaults returned by the API are ignored to avoid perpetual drift.
- Task
Type string - must be one of [
sparse_embedding,text_embedding,rerank,completion,chat_completion,embedding]
- Chunking
Settings string - Configuration for chunking input text, as a JSON object. Applicable only for embedding task types.
- Elasticsearch
Connections []ElasticsearchInference Endpoint Elasticsearch Connection Args - Elasticsearch connection configuration block.
- Inference
Id string - The unique identifier of the inference endpoint.
- Service string
- The service type for the inference endpoint (e.g.
openai,cohere,elasticsearch). - Service
Settings string - Settings specific to the service provider, as a JSON object. May include credentials and model identifiers.
- Task
Settings string - Task-specific settings, as a JSON object. Optional and service-dependent. Only keys explicitly set here are tracked; server-applied defaults returned by the API are ignored to avoid perpetual drift.
- Task
Type string - must be one of [
sparse_embedding,text_embedding,rerank,completion,chat_completion,embedding]
- chunking_
settings string - Configuration for chunking input text, as a JSON object. Applicable only for embedding task types.
- elasticsearch_
connections list(object) - Elasticsearch connection configuration block.
- inference_
id string - The unique identifier of the inference endpoint.
- service string
- The service type for the inference endpoint (e.g.
openai,cohere,elasticsearch). - service_
settings string - Settings specific to the service provider, as a JSON object. May include credentials and model identifiers.
- task_
settings string - Task-specific settings, as a JSON object. Optional and service-dependent. Only keys explicitly set here are tracked; server-applied defaults returned by the API are ignored to avoid perpetual drift.
- task_
type string - must be one of [
sparse_embedding,text_embedding,rerank,completion,chat_completion,embedding]
- chunking
Settings String - Configuration for chunking input text, as a JSON object. Applicable only for embedding task types.
- elasticsearch
Connections List<ElasticsearchInference Endpoint Elasticsearch Connection> - Elasticsearch connection configuration block.
- inference
Id String - The unique identifier of the inference endpoint.
- service String
- The service type for the inference endpoint (e.g.
openai,cohere,elasticsearch). - service
Settings String - Settings specific to the service provider, as a JSON object. May include credentials and model identifiers.
- task
Settings String - Task-specific settings, as a JSON object. Optional and service-dependent. Only keys explicitly set here are tracked; server-applied defaults returned by the API are ignored to avoid perpetual drift.
- task
Type String - must be one of [
sparse_embedding,text_embedding,rerank,completion,chat_completion,embedding]
- chunking
Settings string - Configuration for chunking input text, as a JSON object. Applicable only for embedding task types.
- elasticsearch
Connections ElasticsearchInference Endpoint Elasticsearch Connection[] - Elasticsearch connection configuration block.
- inference
Id string - The unique identifier of the inference endpoint.
- service string
- The service type for the inference endpoint (e.g.
openai,cohere,elasticsearch). - service
Settings string - Settings specific to the service provider, as a JSON object. May include credentials and model identifiers.
- task
Settings string - Task-specific settings, as a JSON object. Optional and service-dependent. Only keys explicitly set here are tracked; server-applied defaults returned by the API are ignored to avoid perpetual drift.
- task
Type string - must be one of [
sparse_embedding,text_embedding,rerank,completion,chat_completion,embedding]
- chunking_
settings str - Configuration for chunking input text, as a JSON object. Applicable only for embedding task types.
- elasticsearch_
connections Sequence[ElasticsearchInference Endpoint Elasticsearch Connection Args] - Elasticsearch connection configuration block.
- inference_
id str - The unique identifier of the inference endpoint.
- service str
- The service type for the inference endpoint (e.g.
openai,cohere,elasticsearch). - service_
settings str - Settings specific to the service provider, as a JSON object. May include credentials and model identifiers.
- task_
settings str - Task-specific settings, as a JSON object. Optional and service-dependent. Only keys explicitly set here are tracked; server-applied defaults returned by the API are ignored to avoid perpetual drift.
- task_
type str - must be one of [
sparse_embedding,text_embedding,rerank,completion,chat_completion,embedding]
- chunking
Settings String - Configuration for chunking input text, as a JSON object. Applicable only for embedding task types.
- elasticsearch
Connections List<Property Map> - Elasticsearch connection configuration block.
- inference
Id String - The unique identifier of the inference endpoint.
- service String
- The service type for the inference endpoint (e.g.
openai,cohere,elasticsearch). - service
Settings String - Settings specific to the service provider, as a JSON object. May include credentials and model identifiers.
- task
Settings String - Task-specific settings, as a JSON object. Optional and service-dependent. Only keys explicitly set here are tracked; server-applied defaults returned by the API are ignored to avoid perpetual drift.
- task
Type String - must be one of [
sparse_embedding,text_embedding,rerank,completion,chat_completion,embedding]
Supporting Types
ElasticsearchInferenceEndpointElasticsearchConnection, ElasticsearchInferenceEndpointElasticsearchConnectionArgs
- 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
- 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
- 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
- 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
- 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
- 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
- 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
- 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 0.15.0
published on Thursday, May 14, 2026 by elastic
published on Thursday, May 14, 2026 by elastic
