We recommend using Azure Native.
azure.machinelearning.InferenceCluster
Explore with Pulumi AI
Manages a Machine Learning Inference Cluster.
NOTE: The Machine Learning Inference Cluster resource is used to attach an existing AKS cluster to the Machine Learning Workspace, it doesn’t create the AKS cluster itself. Therefore it can only be created and deleted, not updated. Any change to the configuration will recreate the resource.
Example Usage
import * as pulumi from "@pulumi/pulumi";
import * as azure from "@pulumi/azure";
const current = azure.core.getClientConfig({});
const example = new azure.core.ResourceGroup("example", {
name: "example-rg",
location: "west europe",
tags: {
stage: "example",
},
});
const exampleInsights = new azure.appinsights.Insights("example", {
name: "example-ai",
location: example.location,
resourceGroupName: example.name,
applicationType: "web",
});
const exampleKeyVault = new azure.keyvault.KeyVault("example", {
name: "example-kv",
location: example.location,
resourceGroupName: example.name,
tenantId: current.then(current => current.tenantId),
skuName: "standard",
purgeProtectionEnabled: true,
});
const exampleAccount = new azure.storage.Account("example", {
name: "examplesa",
location: example.location,
resourceGroupName: example.name,
accountTier: "Standard",
accountReplicationType: "LRS",
});
const exampleWorkspace = new azure.machinelearning.Workspace("example", {
name: "example-mlw",
location: example.location,
resourceGroupName: example.name,
applicationInsightsId: exampleInsights.id,
keyVaultId: exampleKeyVault.id,
storageAccountId: exampleAccount.id,
identity: {
type: "SystemAssigned",
},
});
const exampleVirtualNetwork = new azure.network.VirtualNetwork("example", {
name: "example-vnet",
addressSpaces: ["10.1.0.0/16"],
location: example.location,
resourceGroupName: example.name,
});
const exampleSubnet = new azure.network.Subnet("example", {
name: "example-subnet",
resourceGroupName: example.name,
virtualNetworkName: exampleVirtualNetwork.name,
addressPrefixes: ["10.1.0.0/24"],
});
const exampleKubernetesCluster = new azure.containerservice.KubernetesCluster("example", {
name: "example-aks",
location: example.location,
resourceGroupName: example.name,
dnsPrefixPrivateCluster: "prefix",
defaultNodePool: {
name: "default",
nodeCount: 3,
vmSize: "Standard_D3_v2",
vnetSubnetId: exampleSubnet.id,
},
identity: {
type: "SystemAssigned",
},
});
const exampleInferenceCluster = new azure.machinelearning.InferenceCluster("example", {
name: "example",
location: example.location,
clusterPurpose: "FastProd",
kubernetesClusterId: exampleKubernetesCluster.id,
description: "This is an example cluster used with Terraform",
machineLearningWorkspaceId: exampleWorkspace.id,
tags: {
stage: "example",
},
});
import pulumi
import pulumi_azure as azure
current = azure.core.get_client_config()
example = azure.core.ResourceGroup("example",
name="example-rg",
location="west europe",
tags={
"stage": "example",
})
example_insights = azure.appinsights.Insights("example",
name="example-ai",
location=example.location,
resource_group_name=example.name,
application_type="web")
example_key_vault = azure.keyvault.KeyVault("example",
name="example-kv",
location=example.location,
resource_group_name=example.name,
tenant_id=current.tenant_id,
sku_name="standard",
purge_protection_enabled=True)
example_account = azure.storage.Account("example",
name="examplesa",
location=example.location,
resource_group_name=example.name,
account_tier="Standard",
account_replication_type="LRS")
example_workspace = azure.machinelearning.Workspace("example",
name="example-mlw",
location=example.location,
resource_group_name=example.name,
application_insights_id=example_insights.id,
key_vault_id=example_key_vault.id,
storage_account_id=example_account.id,
identity={
"type": "SystemAssigned",
})
example_virtual_network = azure.network.VirtualNetwork("example",
name="example-vnet",
address_spaces=["10.1.0.0/16"],
location=example.location,
resource_group_name=example.name)
example_subnet = azure.network.Subnet("example",
name="example-subnet",
resource_group_name=example.name,
virtual_network_name=example_virtual_network.name,
address_prefixes=["10.1.0.0/24"])
example_kubernetes_cluster = azure.containerservice.KubernetesCluster("example",
name="example-aks",
location=example.location,
resource_group_name=example.name,
dns_prefix_private_cluster="prefix",
default_node_pool={
"name": "default",
"node_count": 3,
"vm_size": "Standard_D3_v2",
"vnet_subnet_id": example_subnet.id,
},
identity={
"type": "SystemAssigned",
})
example_inference_cluster = azure.machinelearning.InferenceCluster("example",
name="example",
location=example.location,
cluster_purpose="FastProd",
kubernetes_cluster_id=example_kubernetes_cluster.id,
description="This is an example cluster used with Terraform",
machine_learning_workspace_id=example_workspace.id,
tags={
"stage": "example",
})
package main
import (
"github.com/pulumi/pulumi-azure/sdk/v6/go/azure/appinsights"
"github.com/pulumi/pulumi-azure/sdk/v6/go/azure/containerservice"
"github.com/pulumi/pulumi-azure/sdk/v6/go/azure/core"
"github.com/pulumi/pulumi-azure/sdk/v6/go/azure/keyvault"
"github.com/pulumi/pulumi-azure/sdk/v6/go/azure/machinelearning"
"github.com/pulumi/pulumi-azure/sdk/v6/go/azure/network"
"github.com/pulumi/pulumi-azure/sdk/v6/go/azure/storage"
"github.com/pulumi/pulumi/sdk/v3/go/pulumi"
)
func main() {
pulumi.Run(func(ctx *pulumi.Context) error {
current, err := core.GetClientConfig(ctx, map[string]interface{}{}, nil)
if err != nil {
return err
}
example, err := core.NewResourceGroup(ctx, "example", &core.ResourceGroupArgs{
Name: pulumi.String("example-rg"),
Location: pulumi.String("west europe"),
Tags: pulumi.StringMap{
"stage": pulumi.String("example"),
},
})
if err != nil {
return err
}
exampleInsights, err := appinsights.NewInsights(ctx, "example", &appinsights.InsightsArgs{
Name: pulumi.String("example-ai"),
Location: example.Location,
ResourceGroupName: example.Name,
ApplicationType: pulumi.String("web"),
})
if err != nil {
return err
}
exampleKeyVault, err := keyvault.NewKeyVault(ctx, "example", &keyvault.KeyVaultArgs{
Name: pulumi.String("example-kv"),
Location: example.Location,
ResourceGroupName: example.Name,
TenantId: pulumi.String(current.TenantId),
SkuName: pulumi.String("standard"),
PurgeProtectionEnabled: pulumi.Bool(true),
})
if err != nil {
return err
}
exampleAccount, err := storage.NewAccount(ctx, "example", &storage.AccountArgs{
Name: pulumi.String("examplesa"),
Location: example.Location,
ResourceGroupName: example.Name,
AccountTier: pulumi.String("Standard"),
AccountReplicationType: pulumi.String("LRS"),
})
if err != nil {
return err
}
exampleWorkspace, err := machinelearning.NewWorkspace(ctx, "example", &machinelearning.WorkspaceArgs{
Name: pulumi.String("example-mlw"),
Location: example.Location,
ResourceGroupName: example.Name,
ApplicationInsightsId: exampleInsights.ID(),
KeyVaultId: exampleKeyVault.ID(),
StorageAccountId: exampleAccount.ID(),
Identity: &machinelearning.WorkspaceIdentityArgs{
Type: pulumi.String("SystemAssigned"),
},
})
if err != nil {
return err
}
exampleVirtualNetwork, err := network.NewVirtualNetwork(ctx, "example", &network.VirtualNetworkArgs{
Name: pulumi.String("example-vnet"),
AddressSpaces: pulumi.StringArray{
pulumi.String("10.1.0.0/16"),
},
Location: example.Location,
ResourceGroupName: example.Name,
})
if err != nil {
return err
}
exampleSubnet, err := network.NewSubnet(ctx, "example", &network.SubnetArgs{
Name: pulumi.String("example-subnet"),
ResourceGroupName: example.Name,
VirtualNetworkName: exampleVirtualNetwork.Name,
AddressPrefixes: pulumi.StringArray{
pulumi.String("10.1.0.0/24"),
},
})
if err != nil {
return err
}
exampleKubernetesCluster, err := containerservice.NewKubernetesCluster(ctx, "example", &containerservice.KubernetesClusterArgs{
Name: pulumi.String("example-aks"),
Location: example.Location,
ResourceGroupName: example.Name,
DnsPrefixPrivateCluster: pulumi.String("prefix"),
DefaultNodePool: &containerservice.KubernetesClusterDefaultNodePoolArgs{
Name: pulumi.String("default"),
NodeCount: pulumi.Int(3),
VmSize: pulumi.String("Standard_D3_v2"),
VnetSubnetId: exampleSubnet.ID(),
},
Identity: &containerservice.KubernetesClusterIdentityArgs{
Type: pulumi.String("SystemAssigned"),
},
})
if err != nil {
return err
}
_, err = machinelearning.NewInferenceCluster(ctx, "example", &machinelearning.InferenceClusterArgs{
Name: pulumi.String("example"),
Location: example.Location,
ClusterPurpose: pulumi.String("FastProd"),
KubernetesClusterId: exampleKubernetesCluster.ID(),
Description: pulumi.String("This is an example cluster used with Terraform"),
MachineLearningWorkspaceId: exampleWorkspace.ID(),
Tags: pulumi.StringMap{
"stage": pulumi.String("example"),
},
})
if err != nil {
return err
}
return nil
})
}
using System.Collections.Generic;
using System.Linq;
using Pulumi;
using Azure = Pulumi.Azure;
return await Deployment.RunAsync(() =>
{
var current = Azure.Core.GetClientConfig.Invoke();
var example = new Azure.Core.ResourceGroup("example", new()
{
Name = "example-rg",
Location = "west europe",
Tags =
{
{ "stage", "example" },
},
});
var exampleInsights = new Azure.AppInsights.Insights("example", new()
{
Name = "example-ai",
Location = example.Location,
ResourceGroupName = example.Name,
ApplicationType = "web",
});
var exampleKeyVault = new Azure.KeyVault.KeyVault("example", new()
{
Name = "example-kv",
Location = example.Location,
ResourceGroupName = example.Name,
TenantId = current.Apply(getClientConfigResult => getClientConfigResult.TenantId),
SkuName = "standard",
PurgeProtectionEnabled = true,
});
var exampleAccount = new Azure.Storage.Account("example", new()
{
Name = "examplesa",
Location = example.Location,
ResourceGroupName = example.Name,
AccountTier = "Standard",
AccountReplicationType = "LRS",
});
var exampleWorkspace = new Azure.MachineLearning.Workspace("example", new()
{
Name = "example-mlw",
Location = example.Location,
ResourceGroupName = example.Name,
ApplicationInsightsId = exampleInsights.Id,
KeyVaultId = exampleKeyVault.Id,
StorageAccountId = exampleAccount.Id,
Identity = new Azure.MachineLearning.Inputs.WorkspaceIdentityArgs
{
Type = "SystemAssigned",
},
});
var exampleVirtualNetwork = new Azure.Network.VirtualNetwork("example", new()
{
Name = "example-vnet",
AddressSpaces = new[]
{
"10.1.0.0/16",
},
Location = example.Location,
ResourceGroupName = example.Name,
});
var exampleSubnet = new Azure.Network.Subnet("example", new()
{
Name = "example-subnet",
ResourceGroupName = example.Name,
VirtualNetworkName = exampleVirtualNetwork.Name,
AddressPrefixes = new[]
{
"10.1.0.0/24",
},
});
var exampleKubernetesCluster = new Azure.ContainerService.KubernetesCluster("example", new()
{
Name = "example-aks",
Location = example.Location,
ResourceGroupName = example.Name,
DnsPrefixPrivateCluster = "prefix",
DefaultNodePool = new Azure.ContainerService.Inputs.KubernetesClusterDefaultNodePoolArgs
{
Name = "default",
NodeCount = 3,
VmSize = "Standard_D3_v2",
VnetSubnetId = exampleSubnet.Id,
},
Identity = new Azure.ContainerService.Inputs.KubernetesClusterIdentityArgs
{
Type = "SystemAssigned",
},
});
var exampleInferenceCluster = new Azure.MachineLearning.InferenceCluster("example", new()
{
Name = "example",
Location = example.Location,
ClusterPurpose = "FastProd",
KubernetesClusterId = exampleKubernetesCluster.Id,
Description = "This is an example cluster used with Terraform",
MachineLearningWorkspaceId = exampleWorkspace.Id,
Tags =
{
{ "stage", "example" },
},
});
});
package generated_program;
import com.pulumi.Context;
import com.pulumi.Pulumi;
import com.pulumi.core.Output;
import com.pulumi.azure.core.CoreFunctions;
import com.pulumi.azure.core.ResourceGroup;
import com.pulumi.azure.core.ResourceGroupArgs;
import com.pulumi.azure.appinsights.Insights;
import com.pulumi.azure.appinsights.InsightsArgs;
import com.pulumi.azure.keyvault.KeyVault;
import com.pulumi.azure.keyvault.KeyVaultArgs;
import com.pulumi.azure.storage.Account;
import com.pulumi.azure.storage.AccountArgs;
import com.pulumi.azure.machinelearning.Workspace;
import com.pulumi.azure.machinelearning.WorkspaceArgs;
import com.pulumi.azure.machinelearning.inputs.WorkspaceIdentityArgs;
import com.pulumi.azure.network.VirtualNetwork;
import com.pulumi.azure.network.VirtualNetworkArgs;
import com.pulumi.azure.network.Subnet;
import com.pulumi.azure.network.SubnetArgs;
import com.pulumi.azure.containerservice.KubernetesCluster;
import com.pulumi.azure.containerservice.KubernetesClusterArgs;
import com.pulumi.azure.containerservice.inputs.KubernetesClusterDefaultNodePoolArgs;
import com.pulumi.azure.containerservice.inputs.KubernetesClusterIdentityArgs;
import com.pulumi.azure.machinelearning.InferenceCluster;
import com.pulumi.azure.machinelearning.InferenceClusterArgs;
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 current = CoreFunctions.getClientConfig();
var example = new ResourceGroup("example", ResourceGroupArgs.builder()
.name("example-rg")
.location("west europe")
.tags(Map.of("stage", "example"))
.build());
var exampleInsights = new Insights("exampleInsights", InsightsArgs.builder()
.name("example-ai")
.location(example.location())
.resourceGroupName(example.name())
.applicationType("web")
.build());
var exampleKeyVault = new KeyVault("exampleKeyVault", KeyVaultArgs.builder()
.name("example-kv")
.location(example.location())
.resourceGroupName(example.name())
.tenantId(current.applyValue(getClientConfigResult -> getClientConfigResult.tenantId()))
.skuName("standard")
.purgeProtectionEnabled(true)
.build());
var exampleAccount = new Account("exampleAccount", AccountArgs.builder()
.name("examplesa")
.location(example.location())
.resourceGroupName(example.name())
.accountTier("Standard")
.accountReplicationType("LRS")
.build());
var exampleWorkspace = new Workspace("exampleWorkspace", WorkspaceArgs.builder()
.name("example-mlw")
.location(example.location())
.resourceGroupName(example.name())
.applicationInsightsId(exampleInsights.id())
.keyVaultId(exampleKeyVault.id())
.storageAccountId(exampleAccount.id())
.identity(WorkspaceIdentityArgs.builder()
.type("SystemAssigned")
.build())
.build());
var exampleVirtualNetwork = new VirtualNetwork("exampleVirtualNetwork", VirtualNetworkArgs.builder()
.name("example-vnet")
.addressSpaces("10.1.0.0/16")
.location(example.location())
.resourceGroupName(example.name())
.build());
var exampleSubnet = new Subnet("exampleSubnet", SubnetArgs.builder()
.name("example-subnet")
.resourceGroupName(example.name())
.virtualNetworkName(exampleVirtualNetwork.name())
.addressPrefixes("10.1.0.0/24")
.build());
var exampleKubernetesCluster = new KubernetesCluster("exampleKubernetesCluster", KubernetesClusterArgs.builder()
.name("example-aks")
.location(example.location())
.resourceGroupName(example.name())
.dnsPrefixPrivateCluster("prefix")
.defaultNodePool(KubernetesClusterDefaultNodePoolArgs.builder()
.name("default")
.nodeCount(3)
.vmSize("Standard_D3_v2")
.vnetSubnetId(exampleSubnet.id())
.build())
.identity(KubernetesClusterIdentityArgs.builder()
.type("SystemAssigned")
.build())
.build());
var exampleInferenceCluster = new InferenceCluster("exampleInferenceCluster", InferenceClusterArgs.builder()
.name("example")
.location(example.location())
.clusterPurpose("FastProd")
.kubernetesClusterId(exampleKubernetesCluster.id())
.description("This is an example cluster used with Terraform")
.machineLearningWorkspaceId(exampleWorkspace.id())
.tags(Map.of("stage", "example"))
.build());
}
}
resources:
example:
type: azure:core:ResourceGroup
properties:
name: example-rg
location: west europe
tags:
stage: example
exampleInsights:
type: azure:appinsights:Insights
name: example
properties:
name: example-ai
location: ${example.location}
resourceGroupName: ${example.name}
applicationType: web
exampleKeyVault:
type: azure:keyvault:KeyVault
name: example
properties:
name: example-kv
location: ${example.location}
resourceGroupName: ${example.name}
tenantId: ${current.tenantId}
skuName: standard
purgeProtectionEnabled: true
exampleAccount:
type: azure:storage:Account
name: example
properties:
name: examplesa
location: ${example.location}
resourceGroupName: ${example.name}
accountTier: Standard
accountReplicationType: LRS
exampleWorkspace:
type: azure:machinelearning:Workspace
name: example
properties:
name: example-mlw
location: ${example.location}
resourceGroupName: ${example.name}
applicationInsightsId: ${exampleInsights.id}
keyVaultId: ${exampleKeyVault.id}
storageAccountId: ${exampleAccount.id}
identity:
type: SystemAssigned
exampleVirtualNetwork:
type: azure:network:VirtualNetwork
name: example
properties:
name: example-vnet
addressSpaces:
- 10.1.0.0/16
location: ${example.location}
resourceGroupName: ${example.name}
exampleSubnet:
type: azure:network:Subnet
name: example
properties:
name: example-subnet
resourceGroupName: ${example.name}
virtualNetworkName: ${exampleVirtualNetwork.name}
addressPrefixes:
- 10.1.0.0/24
exampleKubernetesCluster:
type: azure:containerservice:KubernetesCluster
name: example
properties:
name: example-aks
location: ${example.location}
resourceGroupName: ${example.name}
dnsPrefixPrivateCluster: prefix
defaultNodePool:
name: default
nodeCount: 3
vmSize: Standard_D3_v2
vnetSubnetId: ${exampleSubnet.id}
identity:
type: SystemAssigned
exampleInferenceCluster:
type: azure:machinelearning:InferenceCluster
name: example
properties:
name: example
location: ${example.location}
clusterPurpose: FastProd
kubernetesClusterId: ${exampleKubernetesCluster.id}
description: This is an example cluster used with Terraform
machineLearningWorkspaceId: ${exampleWorkspace.id}
tags:
stage: example
variables:
current:
fn::invoke:
Function: azure:core:getClientConfig
Arguments: {}
Create InferenceCluster Resource
Resources are created with functions called constructors. To learn more about declaring and configuring resources, see Resources.
Constructor syntax
new InferenceCluster(name: string, args: InferenceClusterArgs, opts?: CustomResourceOptions);
@overload
def InferenceCluster(resource_name: str,
args: InferenceClusterArgs,
opts: Optional[ResourceOptions] = None)
@overload
def InferenceCluster(resource_name: str,
opts: Optional[ResourceOptions] = None,
kubernetes_cluster_id: Optional[str] = None,
machine_learning_workspace_id: Optional[str] = None,
cluster_purpose: Optional[str] = None,
description: Optional[str] = None,
identity: Optional[InferenceClusterIdentityArgs] = None,
location: Optional[str] = None,
name: Optional[str] = None,
ssl: Optional[InferenceClusterSslArgs] = None,
tags: Optional[Mapping[str, str]] = None)
func NewInferenceCluster(ctx *Context, name string, args InferenceClusterArgs, opts ...ResourceOption) (*InferenceCluster, error)
public InferenceCluster(string name, InferenceClusterArgs args, CustomResourceOptions? opts = null)
public InferenceCluster(String name, InferenceClusterArgs args)
public InferenceCluster(String name, InferenceClusterArgs args, CustomResourceOptions options)
type: azure:machinelearning:InferenceCluster
properties: # The arguments to resource properties.
options: # Bag of options to control resource's behavior.
Parameters
- name string
- The unique name of the resource.
- args InferenceClusterArgs
- 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 InferenceClusterArgs
- 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 InferenceClusterArgs
- The arguments to resource properties.
- opts ResourceOption
- Bag of options to control resource's behavior.
- name string
- The unique name of the resource.
- args InferenceClusterArgs
- The arguments to resource properties.
- opts CustomResourceOptions
- Bag of options to control resource's behavior.
- name String
- The unique name of the resource.
- args InferenceClusterArgs
- 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 inferenceClusterResource = new Azure.MachineLearning.InferenceCluster("inferenceClusterResource", new()
{
KubernetesClusterId = "string",
MachineLearningWorkspaceId = "string",
ClusterPurpose = "string",
Description = "string",
Identity = new Azure.MachineLearning.Inputs.InferenceClusterIdentityArgs
{
Type = "string",
IdentityIds = new[]
{
"string",
},
PrincipalId = "string",
TenantId = "string",
},
Location = "string",
Name = "string",
Ssl = new Azure.MachineLearning.Inputs.InferenceClusterSslArgs
{
Cert = "string",
Cname = "string",
Key = "string",
LeafDomainLabel = "string",
OverwriteExistingDomain = false,
},
Tags =
{
{ "string", "string" },
},
});
example, err := machinelearning.NewInferenceCluster(ctx, "inferenceClusterResource", &machinelearning.InferenceClusterArgs{
KubernetesClusterId: pulumi.String("string"),
MachineLearningWorkspaceId: pulumi.String("string"),
ClusterPurpose: pulumi.String("string"),
Description: pulumi.String("string"),
Identity: &machinelearning.InferenceClusterIdentityArgs{
Type: pulumi.String("string"),
IdentityIds: pulumi.StringArray{
pulumi.String("string"),
},
PrincipalId: pulumi.String("string"),
TenantId: pulumi.String("string"),
},
Location: pulumi.String("string"),
Name: pulumi.String("string"),
Ssl: &machinelearning.InferenceClusterSslArgs{
Cert: pulumi.String("string"),
Cname: pulumi.String("string"),
Key: pulumi.String("string"),
LeafDomainLabel: pulumi.String("string"),
OverwriteExistingDomain: pulumi.Bool(false),
},
Tags: pulumi.StringMap{
"string": pulumi.String("string"),
},
})
var inferenceClusterResource = new InferenceCluster("inferenceClusterResource", InferenceClusterArgs.builder()
.kubernetesClusterId("string")
.machineLearningWorkspaceId("string")
.clusterPurpose("string")
.description("string")
.identity(InferenceClusterIdentityArgs.builder()
.type("string")
.identityIds("string")
.principalId("string")
.tenantId("string")
.build())
.location("string")
.name("string")
.ssl(InferenceClusterSslArgs.builder()
.cert("string")
.cname("string")
.key("string")
.leafDomainLabel("string")
.overwriteExistingDomain(false)
.build())
.tags(Map.of("string", "string"))
.build());
inference_cluster_resource = azure.machinelearning.InferenceCluster("inferenceClusterResource",
kubernetes_cluster_id="string",
machine_learning_workspace_id="string",
cluster_purpose="string",
description="string",
identity={
"type": "string",
"identity_ids": ["string"],
"principal_id": "string",
"tenant_id": "string",
},
location="string",
name="string",
ssl={
"cert": "string",
"cname": "string",
"key": "string",
"leaf_domain_label": "string",
"overwrite_existing_domain": False,
},
tags={
"string": "string",
})
const inferenceClusterResource = new azure.machinelearning.InferenceCluster("inferenceClusterResource", {
kubernetesClusterId: "string",
machineLearningWorkspaceId: "string",
clusterPurpose: "string",
description: "string",
identity: {
type: "string",
identityIds: ["string"],
principalId: "string",
tenantId: "string",
},
location: "string",
name: "string",
ssl: {
cert: "string",
cname: "string",
key: "string",
leafDomainLabel: "string",
overwriteExistingDomain: false,
},
tags: {
string: "string",
},
});
type: azure:machinelearning:InferenceCluster
properties:
clusterPurpose: string
description: string
identity:
identityIds:
- string
principalId: string
tenantId: string
type: string
kubernetesClusterId: string
location: string
machineLearningWorkspaceId: string
name: string
ssl:
cert: string
cname: string
key: string
leafDomainLabel: string
overwriteExistingDomain: false
tags:
string: string
InferenceCluster 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 InferenceCluster resource accepts the following input properties:
- Kubernetes
Cluster stringId - The ID of the Kubernetes Cluster. Changing this forces a new Machine Learning Inference Cluster to be created.
- Machine
Learning stringWorkspace Id - The ID of the Machine Learning Workspace. Changing this forces a new Machine Learning Inference Cluster to be created.
- Cluster
Purpose string The purpose of the Inference Cluster. Options are
DevTest
,DenseProd
andFastProd
. If used for Development or Testing, useDevTest
here. Default purpose isFastProd
, which is recommended for production workloads. Changing this forces a new Machine Learning Inference Cluster to be created.NOTE: When creating or attaching a cluster, if the cluster will be used for production (
cluster_purpose = "FastProd"
), then it must contain at least 12 virtual CPUs. The number of virtual CPUs can be calculated by multiplying the number of nodes in the cluster by the number of cores provided by the VM size selected. For example, if you use a VM size of "Standard_D3_v2", which has 4 virtual cores, then you should select 3 or greater as the number of nodes.- Description string
- The description of the Machine Learning Inference Cluster. Changing this forces a new Machine Learning Inference Cluster to be created.
- Identity
Inference
Cluster Identity - An
identity
block as defined below. Changing this forces a new Machine Learning Inference Cluster to be created. - Location string
- The Azure Region where the Machine Learning Inference Cluster should exist. Changing this forces a new Machine Learning Inference Cluster to be created.
- Name string
- The name which should be used for this Machine Learning Inference Cluster. Changing this forces a new Machine Learning Inference Cluster to be created.
- Ssl
Inference
Cluster Ssl - A
ssl
block as defined below. Changing this forces a new Machine Learning Inference Cluster to be created. - Dictionary<string, string>
- A mapping of tags which should be assigned to the Machine Learning Inference Cluster. Changing this forces a new Machine Learning Inference Cluster to be created.
- Kubernetes
Cluster stringId - The ID of the Kubernetes Cluster. Changing this forces a new Machine Learning Inference Cluster to be created.
- Machine
Learning stringWorkspace Id - The ID of the Machine Learning Workspace. Changing this forces a new Machine Learning Inference Cluster to be created.
- Cluster
Purpose string The purpose of the Inference Cluster. Options are
DevTest
,DenseProd
andFastProd
. If used for Development or Testing, useDevTest
here. Default purpose isFastProd
, which is recommended for production workloads. Changing this forces a new Machine Learning Inference Cluster to be created.NOTE: When creating or attaching a cluster, if the cluster will be used for production (
cluster_purpose = "FastProd"
), then it must contain at least 12 virtual CPUs. The number of virtual CPUs can be calculated by multiplying the number of nodes in the cluster by the number of cores provided by the VM size selected. For example, if you use a VM size of "Standard_D3_v2", which has 4 virtual cores, then you should select 3 or greater as the number of nodes.- Description string
- The description of the Machine Learning Inference Cluster. Changing this forces a new Machine Learning Inference Cluster to be created.
- Identity
Inference
Cluster Identity Args - An
identity
block as defined below. Changing this forces a new Machine Learning Inference Cluster to be created. - Location string
- The Azure Region where the Machine Learning Inference Cluster should exist. Changing this forces a new Machine Learning Inference Cluster to be created.
- Name string
- The name which should be used for this Machine Learning Inference Cluster. Changing this forces a new Machine Learning Inference Cluster to be created.
- Ssl
Inference
Cluster Ssl Args - A
ssl
block as defined below. Changing this forces a new Machine Learning Inference Cluster to be created. - map[string]string
- A mapping of tags which should be assigned to the Machine Learning Inference Cluster. Changing this forces a new Machine Learning Inference Cluster to be created.
- kubernetes
Cluster StringId - The ID of the Kubernetes Cluster. Changing this forces a new Machine Learning Inference Cluster to be created.
- machine
Learning StringWorkspace Id - The ID of the Machine Learning Workspace. Changing this forces a new Machine Learning Inference Cluster to be created.
- cluster
Purpose String The purpose of the Inference Cluster. Options are
DevTest
,DenseProd
andFastProd
. If used for Development or Testing, useDevTest
here. Default purpose isFastProd
, which is recommended for production workloads. Changing this forces a new Machine Learning Inference Cluster to be created.NOTE: When creating or attaching a cluster, if the cluster will be used for production (
cluster_purpose = "FastProd"
), then it must contain at least 12 virtual CPUs. The number of virtual CPUs can be calculated by multiplying the number of nodes in the cluster by the number of cores provided by the VM size selected. For example, if you use a VM size of "Standard_D3_v2", which has 4 virtual cores, then you should select 3 or greater as the number of nodes.- description String
- The description of the Machine Learning Inference Cluster. Changing this forces a new Machine Learning Inference Cluster to be created.
- identity
Inference
Cluster Identity - An
identity
block as defined below. Changing this forces a new Machine Learning Inference Cluster to be created. - location String
- The Azure Region where the Machine Learning Inference Cluster should exist. Changing this forces a new Machine Learning Inference Cluster to be created.
- name String
- The name which should be used for this Machine Learning Inference Cluster. Changing this forces a new Machine Learning Inference Cluster to be created.
- ssl
Inference
Cluster Ssl - A
ssl
block as defined below. Changing this forces a new Machine Learning Inference Cluster to be created. - Map<String,String>
- A mapping of tags which should be assigned to the Machine Learning Inference Cluster. Changing this forces a new Machine Learning Inference Cluster to be created.
- kubernetes
Cluster stringId - The ID of the Kubernetes Cluster. Changing this forces a new Machine Learning Inference Cluster to be created.
- machine
Learning stringWorkspace Id - The ID of the Machine Learning Workspace. Changing this forces a new Machine Learning Inference Cluster to be created.
- cluster
Purpose string The purpose of the Inference Cluster. Options are
DevTest
,DenseProd
andFastProd
. If used for Development or Testing, useDevTest
here. Default purpose isFastProd
, which is recommended for production workloads. Changing this forces a new Machine Learning Inference Cluster to be created.NOTE: When creating or attaching a cluster, if the cluster will be used for production (
cluster_purpose = "FastProd"
), then it must contain at least 12 virtual CPUs. The number of virtual CPUs can be calculated by multiplying the number of nodes in the cluster by the number of cores provided by the VM size selected. For example, if you use a VM size of "Standard_D3_v2", which has 4 virtual cores, then you should select 3 or greater as the number of nodes.- description string
- The description of the Machine Learning Inference Cluster. Changing this forces a new Machine Learning Inference Cluster to be created.
- identity
Inference
Cluster Identity - An
identity
block as defined below. Changing this forces a new Machine Learning Inference Cluster to be created. - location string
- The Azure Region where the Machine Learning Inference Cluster should exist. Changing this forces a new Machine Learning Inference Cluster to be created.
- name string
- The name which should be used for this Machine Learning Inference Cluster. Changing this forces a new Machine Learning Inference Cluster to be created.
- ssl
Inference
Cluster Ssl - A
ssl
block as defined below. Changing this forces a new Machine Learning Inference Cluster to be created. - {[key: string]: string}
- A mapping of tags which should be assigned to the Machine Learning Inference Cluster. Changing this forces a new Machine Learning Inference Cluster to be created.
- kubernetes_
cluster_ strid - The ID of the Kubernetes Cluster. Changing this forces a new Machine Learning Inference Cluster to be created.
- machine_
learning_ strworkspace_ id - The ID of the Machine Learning Workspace. Changing this forces a new Machine Learning Inference Cluster to be created.
- cluster_
purpose str The purpose of the Inference Cluster. Options are
DevTest
,DenseProd
andFastProd
. If used for Development or Testing, useDevTest
here. Default purpose isFastProd
, which is recommended for production workloads. Changing this forces a new Machine Learning Inference Cluster to be created.NOTE: When creating or attaching a cluster, if the cluster will be used for production (
cluster_purpose = "FastProd"
), then it must contain at least 12 virtual CPUs. The number of virtual CPUs can be calculated by multiplying the number of nodes in the cluster by the number of cores provided by the VM size selected. For example, if you use a VM size of "Standard_D3_v2", which has 4 virtual cores, then you should select 3 or greater as the number of nodes.- description str
- The description of the Machine Learning Inference Cluster. Changing this forces a new Machine Learning Inference Cluster to be created.
- identity
Inference
Cluster Identity Args - An
identity
block as defined below. Changing this forces a new Machine Learning Inference Cluster to be created. - location str
- The Azure Region where the Machine Learning Inference Cluster should exist. Changing this forces a new Machine Learning Inference Cluster to be created.
- name str
- The name which should be used for this Machine Learning Inference Cluster. Changing this forces a new Machine Learning Inference Cluster to be created.
- ssl
Inference
Cluster Ssl Args - A
ssl
block as defined below. Changing this forces a new Machine Learning Inference Cluster to be created. - Mapping[str, str]
- A mapping of tags which should be assigned to the Machine Learning Inference Cluster. Changing this forces a new Machine Learning Inference Cluster to be created.
- kubernetes
Cluster StringId - The ID of the Kubernetes Cluster. Changing this forces a new Machine Learning Inference Cluster to be created.
- machine
Learning StringWorkspace Id - The ID of the Machine Learning Workspace. Changing this forces a new Machine Learning Inference Cluster to be created.
- cluster
Purpose String The purpose of the Inference Cluster. Options are
DevTest
,DenseProd
andFastProd
. If used for Development or Testing, useDevTest
here. Default purpose isFastProd
, which is recommended for production workloads. Changing this forces a new Machine Learning Inference Cluster to be created.NOTE: When creating or attaching a cluster, if the cluster will be used for production (
cluster_purpose = "FastProd"
), then it must contain at least 12 virtual CPUs. The number of virtual CPUs can be calculated by multiplying the number of nodes in the cluster by the number of cores provided by the VM size selected. For example, if you use a VM size of "Standard_D3_v2", which has 4 virtual cores, then you should select 3 or greater as the number of nodes.- description String
- The description of the Machine Learning Inference Cluster. Changing this forces a new Machine Learning Inference Cluster to be created.
- identity Property Map
- An
identity
block as defined below. Changing this forces a new Machine Learning Inference Cluster to be created. - location String
- The Azure Region where the Machine Learning Inference Cluster should exist. Changing this forces a new Machine Learning Inference Cluster to be created.
- name String
- The name which should be used for this Machine Learning Inference Cluster. Changing this forces a new Machine Learning Inference Cluster to be created.
- ssl Property Map
- A
ssl
block as defined below. Changing this forces a new Machine Learning Inference Cluster to be created. - Map<String>
- A mapping of tags which should be assigned to the Machine Learning Inference Cluster. Changing this forces a new Machine Learning Inference Cluster to be created.
Outputs
All input properties are implicitly available as output properties. Additionally, the InferenceCluster 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 str
- The provider-assigned unique ID for this managed resource.
- id String
- The provider-assigned unique ID for this managed resource.
Look up Existing InferenceCluster Resource
Get an existing InferenceCluster 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?: InferenceClusterState, opts?: CustomResourceOptions): InferenceCluster
@staticmethod
def get(resource_name: str,
id: str,
opts: Optional[ResourceOptions] = None,
cluster_purpose: Optional[str] = None,
description: Optional[str] = None,
identity: Optional[InferenceClusterIdentityArgs] = None,
kubernetes_cluster_id: Optional[str] = None,
location: Optional[str] = None,
machine_learning_workspace_id: Optional[str] = None,
name: Optional[str] = None,
ssl: Optional[InferenceClusterSslArgs] = None,
tags: Optional[Mapping[str, str]] = None) -> InferenceCluster
func GetInferenceCluster(ctx *Context, name string, id IDInput, state *InferenceClusterState, opts ...ResourceOption) (*InferenceCluster, error)
public static InferenceCluster Get(string name, Input<string> id, InferenceClusterState? state, CustomResourceOptions? opts = null)
public static InferenceCluster get(String name, Output<String> id, InferenceClusterState state, CustomResourceOptions options)
Resource lookup is not supported in YAML
- 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.
- Cluster
Purpose string The purpose of the Inference Cluster. Options are
DevTest
,DenseProd
andFastProd
. If used for Development or Testing, useDevTest
here. Default purpose isFastProd
, which is recommended for production workloads. Changing this forces a new Machine Learning Inference Cluster to be created.NOTE: When creating or attaching a cluster, if the cluster will be used for production (
cluster_purpose = "FastProd"
), then it must contain at least 12 virtual CPUs. The number of virtual CPUs can be calculated by multiplying the number of nodes in the cluster by the number of cores provided by the VM size selected. For example, if you use a VM size of "Standard_D3_v2", which has 4 virtual cores, then you should select 3 or greater as the number of nodes.- Description string
- The description of the Machine Learning Inference Cluster. Changing this forces a new Machine Learning Inference Cluster to be created.
- Identity
Inference
Cluster Identity - An
identity
block as defined below. Changing this forces a new Machine Learning Inference Cluster to be created. - Kubernetes
Cluster stringId - The ID of the Kubernetes Cluster. Changing this forces a new Machine Learning Inference Cluster to be created.
- Location string
- The Azure Region where the Machine Learning Inference Cluster should exist. Changing this forces a new Machine Learning Inference Cluster to be created.
- Machine
Learning stringWorkspace Id - The ID of the Machine Learning Workspace. Changing this forces a new Machine Learning Inference Cluster to be created.
- Name string
- The name which should be used for this Machine Learning Inference Cluster. Changing this forces a new Machine Learning Inference Cluster to be created.
- Ssl
Inference
Cluster Ssl - A
ssl
block as defined below. Changing this forces a new Machine Learning Inference Cluster to be created. - Dictionary<string, string>
- A mapping of tags which should be assigned to the Machine Learning Inference Cluster. Changing this forces a new Machine Learning Inference Cluster to be created.
- Cluster
Purpose string The purpose of the Inference Cluster. Options are
DevTest
,DenseProd
andFastProd
. If used for Development or Testing, useDevTest
here. Default purpose isFastProd
, which is recommended for production workloads. Changing this forces a new Machine Learning Inference Cluster to be created.NOTE: When creating or attaching a cluster, if the cluster will be used for production (
cluster_purpose = "FastProd"
), then it must contain at least 12 virtual CPUs. The number of virtual CPUs can be calculated by multiplying the number of nodes in the cluster by the number of cores provided by the VM size selected. For example, if you use a VM size of "Standard_D3_v2", which has 4 virtual cores, then you should select 3 or greater as the number of nodes.- Description string
- The description of the Machine Learning Inference Cluster. Changing this forces a new Machine Learning Inference Cluster to be created.
- Identity
Inference
Cluster Identity Args - An
identity
block as defined below. Changing this forces a new Machine Learning Inference Cluster to be created. - Kubernetes
Cluster stringId - The ID of the Kubernetes Cluster. Changing this forces a new Machine Learning Inference Cluster to be created.
- Location string
- The Azure Region where the Machine Learning Inference Cluster should exist. Changing this forces a new Machine Learning Inference Cluster to be created.
- Machine
Learning stringWorkspace Id - The ID of the Machine Learning Workspace. Changing this forces a new Machine Learning Inference Cluster to be created.
- Name string
- The name which should be used for this Machine Learning Inference Cluster. Changing this forces a new Machine Learning Inference Cluster to be created.
- Ssl
Inference
Cluster Ssl Args - A
ssl
block as defined below. Changing this forces a new Machine Learning Inference Cluster to be created. - map[string]string
- A mapping of tags which should be assigned to the Machine Learning Inference Cluster. Changing this forces a new Machine Learning Inference Cluster to be created.
- cluster
Purpose String The purpose of the Inference Cluster. Options are
DevTest
,DenseProd
andFastProd
. If used for Development or Testing, useDevTest
here. Default purpose isFastProd
, which is recommended for production workloads. Changing this forces a new Machine Learning Inference Cluster to be created.NOTE: When creating or attaching a cluster, if the cluster will be used for production (
cluster_purpose = "FastProd"
), then it must contain at least 12 virtual CPUs. The number of virtual CPUs can be calculated by multiplying the number of nodes in the cluster by the number of cores provided by the VM size selected. For example, if you use a VM size of "Standard_D3_v2", which has 4 virtual cores, then you should select 3 or greater as the number of nodes.- description String
- The description of the Machine Learning Inference Cluster. Changing this forces a new Machine Learning Inference Cluster to be created.
- identity
Inference
Cluster Identity - An
identity
block as defined below. Changing this forces a new Machine Learning Inference Cluster to be created. - kubernetes
Cluster StringId - The ID of the Kubernetes Cluster. Changing this forces a new Machine Learning Inference Cluster to be created.
- location String
- The Azure Region where the Machine Learning Inference Cluster should exist. Changing this forces a new Machine Learning Inference Cluster to be created.
- machine
Learning StringWorkspace Id - The ID of the Machine Learning Workspace. Changing this forces a new Machine Learning Inference Cluster to be created.
- name String
- The name which should be used for this Machine Learning Inference Cluster. Changing this forces a new Machine Learning Inference Cluster to be created.
- ssl
Inference
Cluster Ssl - A
ssl
block as defined below. Changing this forces a new Machine Learning Inference Cluster to be created. - Map<String,String>
- A mapping of tags which should be assigned to the Machine Learning Inference Cluster. Changing this forces a new Machine Learning Inference Cluster to be created.
- cluster
Purpose string The purpose of the Inference Cluster. Options are
DevTest
,DenseProd
andFastProd
. If used for Development or Testing, useDevTest
here. Default purpose isFastProd
, which is recommended for production workloads. Changing this forces a new Machine Learning Inference Cluster to be created.NOTE: When creating or attaching a cluster, if the cluster will be used for production (
cluster_purpose = "FastProd"
), then it must contain at least 12 virtual CPUs. The number of virtual CPUs can be calculated by multiplying the number of nodes in the cluster by the number of cores provided by the VM size selected. For example, if you use a VM size of "Standard_D3_v2", which has 4 virtual cores, then you should select 3 or greater as the number of nodes.- description string
- The description of the Machine Learning Inference Cluster. Changing this forces a new Machine Learning Inference Cluster to be created.
- identity
Inference
Cluster Identity - An
identity
block as defined below. Changing this forces a new Machine Learning Inference Cluster to be created. - kubernetes
Cluster stringId - The ID of the Kubernetes Cluster. Changing this forces a new Machine Learning Inference Cluster to be created.
- location string
- The Azure Region where the Machine Learning Inference Cluster should exist. Changing this forces a new Machine Learning Inference Cluster to be created.
- machine
Learning stringWorkspace Id - The ID of the Machine Learning Workspace. Changing this forces a new Machine Learning Inference Cluster to be created.
- name string
- The name which should be used for this Machine Learning Inference Cluster. Changing this forces a new Machine Learning Inference Cluster to be created.
- ssl
Inference
Cluster Ssl - A
ssl
block as defined below. Changing this forces a new Machine Learning Inference Cluster to be created. - {[key: string]: string}
- A mapping of tags which should be assigned to the Machine Learning Inference Cluster. Changing this forces a new Machine Learning Inference Cluster to be created.
- cluster_
purpose str The purpose of the Inference Cluster. Options are
DevTest
,DenseProd
andFastProd
. If used for Development or Testing, useDevTest
here. Default purpose isFastProd
, which is recommended for production workloads. Changing this forces a new Machine Learning Inference Cluster to be created.NOTE: When creating or attaching a cluster, if the cluster will be used for production (
cluster_purpose = "FastProd"
), then it must contain at least 12 virtual CPUs. The number of virtual CPUs can be calculated by multiplying the number of nodes in the cluster by the number of cores provided by the VM size selected. For example, if you use a VM size of "Standard_D3_v2", which has 4 virtual cores, then you should select 3 or greater as the number of nodes.- description str
- The description of the Machine Learning Inference Cluster. Changing this forces a new Machine Learning Inference Cluster to be created.
- identity
Inference
Cluster Identity Args - An
identity
block as defined below. Changing this forces a new Machine Learning Inference Cluster to be created. - kubernetes_
cluster_ strid - The ID of the Kubernetes Cluster. Changing this forces a new Machine Learning Inference Cluster to be created.
- location str
- The Azure Region where the Machine Learning Inference Cluster should exist. Changing this forces a new Machine Learning Inference Cluster to be created.
- machine_
learning_ strworkspace_ id - The ID of the Machine Learning Workspace. Changing this forces a new Machine Learning Inference Cluster to be created.
- name str
- The name which should be used for this Machine Learning Inference Cluster. Changing this forces a new Machine Learning Inference Cluster to be created.
- ssl
Inference
Cluster Ssl Args - A
ssl
block as defined below. Changing this forces a new Machine Learning Inference Cluster to be created. - Mapping[str, str]
- A mapping of tags which should be assigned to the Machine Learning Inference Cluster. Changing this forces a new Machine Learning Inference Cluster to be created.
- cluster
Purpose String The purpose of the Inference Cluster. Options are
DevTest
,DenseProd
andFastProd
. If used for Development or Testing, useDevTest
here. Default purpose isFastProd
, which is recommended for production workloads. Changing this forces a new Machine Learning Inference Cluster to be created.NOTE: When creating or attaching a cluster, if the cluster will be used for production (
cluster_purpose = "FastProd"
), then it must contain at least 12 virtual CPUs. The number of virtual CPUs can be calculated by multiplying the number of nodes in the cluster by the number of cores provided by the VM size selected. For example, if you use a VM size of "Standard_D3_v2", which has 4 virtual cores, then you should select 3 or greater as the number of nodes.- description String
- The description of the Machine Learning Inference Cluster. Changing this forces a new Machine Learning Inference Cluster to be created.
- identity Property Map
- An
identity
block as defined below. Changing this forces a new Machine Learning Inference Cluster to be created. - kubernetes
Cluster StringId - The ID of the Kubernetes Cluster. Changing this forces a new Machine Learning Inference Cluster to be created.
- location String
- The Azure Region where the Machine Learning Inference Cluster should exist. Changing this forces a new Machine Learning Inference Cluster to be created.
- machine
Learning StringWorkspace Id - The ID of the Machine Learning Workspace. Changing this forces a new Machine Learning Inference Cluster to be created.
- name String
- The name which should be used for this Machine Learning Inference Cluster. Changing this forces a new Machine Learning Inference Cluster to be created.
- ssl Property Map
- A
ssl
block as defined below. Changing this forces a new Machine Learning Inference Cluster to be created. - Map<String>
- A mapping of tags which should be assigned to the Machine Learning Inference Cluster. Changing this forces a new Machine Learning Inference Cluster to be created.
Supporting Types
InferenceClusterIdentity, InferenceClusterIdentityArgs
- Type string
- Specifies the type of Managed Service Identity that should be configured on this Machine Learning Inference Cluster. Possible values are
SystemAssigned
,UserAssigned
,SystemAssigned, UserAssigned
(to enable both). Changing this forces a new resource to be created. - Identity
Ids List<string> Specifies a list of User Assigned Managed Identity IDs to be assigned to this Machine Learning Inference Cluster. Changing this forces a new resource to be created.
NOTE: This is required when
type
is set toUserAssigned
orSystemAssigned, UserAssigned
.- Principal
Id string - The Principal ID for the Service Principal associated with the Managed Service Identity of this Machine Learning Inference Cluster.
- Tenant
Id string - The Tenant ID for the Service Principal associated with the Managed Service Identity of this Machine Learning Inference Cluster.
- Type string
- Specifies the type of Managed Service Identity that should be configured on this Machine Learning Inference Cluster. Possible values are
SystemAssigned
,UserAssigned
,SystemAssigned, UserAssigned
(to enable both). Changing this forces a new resource to be created. - Identity
Ids []string Specifies a list of User Assigned Managed Identity IDs to be assigned to this Machine Learning Inference Cluster. Changing this forces a new resource to be created.
NOTE: This is required when
type
is set toUserAssigned
orSystemAssigned, UserAssigned
.- Principal
Id string - The Principal ID for the Service Principal associated with the Managed Service Identity of this Machine Learning Inference Cluster.
- Tenant
Id string - The Tenant ID for the Service Principal associated with the Managed Service Identity of this Machine Learning Inference Cluster.
- type String
- Specifies the type of Managed Service Identity that should be configured on this Machine Learning Inference Cluster. Possible values are
SystemAssigned
,UserAssigned
,SystemAssigned, UserAssigned
(to enable both). Changing this forces a new resource to be created. - identity
Ids List<String> Specifies a list of User Assigned Managed Identity IDs to be assigned to this Machine Learning Inference Cluster. Changing this forces a new resource to be created.
NOTE: This is required when
type
is set toUserAssigned
orSystemAssigned, UserAssigned
.- principal
Id String - The Principal ID for the Service Principal associated with the Managed Service Identity of this Machine Learning Inference Cluster.
- tenant
Id String - The Tenant ID for the Service Principal associated with the Managed Service Identity of this Machine Learning Inference Cluster.
- type string
- Specifies the type of Managed Service Identity that should be configured on this Machine Learning Inference Cluster. Possible values are
SystemAssigned
,UserAssigned
,SystemAssigned, UserAssigned
(to enable both). Changing this forces a new resource to be created. - identity
Ids string[] Specifies a list of User Assigned Managed Identity IDs to be assigned to this Machine Learning Inference Cluster. Changing this forces a new resource to be created.
NOTE: This is required when
type
is set toUserAssigned
orSystemAssigned, UserAssigned
.- principal
Id string - The Principal ID for the Service Principal associated with the Managed Service Identity of this Machine Learning Inference Cluster.
- tenant
Id string - The Tenant ID for the Service Principal associated with the Managed Service Identity of this Machine Learning Inference Cluster.
- type str
- Specifies the type of Managed Service Identity that should be configured on this Machine Learning Inference Cluster. Possible values are
SystemAssigned
,UserAssigned
,SystemAssigned, UserAssigned
(to enable both). Changing this forces a new resource to be created. - identity_
ids Sequence[str] Specifies a list of User Assigned Managed Identity IDs to be assigned to this Machine Learning Inference Cluster. Changing this forces a new resource to be created.
NOTE: This is required when
type
is set toUserAssigned
orSystemAssigned, UserAssigned
.- principal_
id str - The Principal ID for the Service Principal associated with the Managed Service Identity of this Machine Learning Inference Cluster.
- tenant_
id str - The Tenant ID for the Service Principal associated with the Managed Service Identity of this Machine Learning Inference Cluster.
- type String
- Specifies the type of Managed Service Identity that should be configured on this Machine Learning Inference Cluster. Possible values are
SystemAssigned
,UserAssigned
,SystemAssigned, UserAssigned
(to enable both). Changing this forces a new resource to be created. - identity
Ids List<String> Specifies a list of User Assigned Managed Identity IDs to be assigned to this Machine Learning Inference Cluster. Changing this forces a new resource to be created.
NOTE: This is required when
type
is set toUserAssigned
orSystemAssigned, UserAssigned
.- principal
Id String - The Principal ID for the Service Principal associated with the Managed Service Identity of this Machine Learning Inference Cluster.
- tenant
Id String - The Tenant ID for the Service Principal associated with the Managed Service Identity of this Machine Learning Inference Cluster.
InferenceClusterSsl, InferenceClusterSslArgs
- Cert string
- The certificate for the SSL configuration.Conflicts with
ssl[0].leaf_domain_label
,ssl[0].overwrite_existing_domain
. Changing this forces a new Machine Learning Inference Cluster to be created. Defaults to""
. - Cname string
- The cname of the SSL configuration.Conflicts with
ssl[0].leaf_domain_label
,ssl[0].overwrite_existing_domain
. Changing this forces a new Machine Learning Inference Cluster to be created. Defaults to""
. - Key string
- The key content for the SSL configuration.Conflicts with
ssl[0].leaf_domain_label
,ssl[0].overwrite_existing_domain
. Changing this forces a new Machine Learning Inference Cluster to be created. Defaults to""
. - Leaf
Domain stringLabel - The leaf domain label for the SSL configuration. Conflicts with
ssl[0].cert
,ssl[0].key
,ssl[0].cname
. Changing this forces a new Machine Learning Inference Cluster to be created. Defaults to""
. - Overwrite
Existing boolDomain - Whether or not to overwrite existing leaf domain. Conflicts with
ssl[0].cert
,ssl[0].key
,ssl[0].cname
Changing this forces a new Machine Learning Inference Cluster to be created. Defaults to""
.
- Cert string
- The certificate for the SSL configuration.Conflicts with
ssl[0].leaf_domain_label
,ssl[0].overwrite_existing_domain
. Changing this forces a new Machine Learning Inference Cluster to be created. Defaults to""
. - Cname string
- The cname of the SSL configuration.Conflicts with
ssl[0].leaf_domain_label
,ssl[0].overwrite_existing_domain
. Changing this forces a new Machine Learning Inference Cluster to be created. Defaults to""
. - Key string
- The key content for the SSL configuration.Conflicts with
ssl[0].leaf_domain_label
,ssl[0].overwrite_existing_domain
. Changing this forces a new Machine Learning Inference Cluster to be created. Defaults to""
. - Leaf
Domain stringLabel - The leaf domain label for the SSL configuration. Conflicts with
ssl[0].cert
,ssl[0].key
,ssl[0].cname
. Changing this forces a new Machine Learning Inference Cluster to be created. Defaults to""
. - Overwrite
Existing boolDomain - Whether or not to overwrite existing leaf domain. Conflicts with
ssl[0].cert
,ssl[0].key
,ssl[0].cname
Changing this forces a new Machine Learning Inference Cluster to be created. Defaults to""
.
- cert String
- The certificate for the SSL configuration.Conflicts with
ssl[0].leaf_domain_label
,ssl[0].overwrite_existing_domain
. Changing this forces a new Machine Learning Inference Cluster to be created. Defaults to""
. - cname String
- The cname of the SSL configuration.Conflicts with
ssl[0].leaf_domain_label
,ssl[0].overwrite_existing_domain
. Changing this forces a new Machine Learning Inference Cluster to be created. Defaults to""
. - key String
- The key content for the SSL configuration.Conflicts with
ssl[0].leaf_domain_label
,ssl[0].overwrite_existing_domain
. Changing this forces a new Machine Learning Inference Cluster to be created. Defaults to""
. - leaf
Domain StringLabel - The leaf domain label for the SSL configuration. Conflicts with
ssl[0].cert
,ssl[0].key
,ssl[0].cname
. Changing this forces a new Machine Learning Inference Cluster to be created. Defaults to""
. - overwrite
Existing BooleanDomain - Whether or not to overwrite existing leaf domain. Conflicts with
ssl[0].cert
,ssl[0].key
,ssl[0].cname
Changing this forces a new Machine Learning Inference Cluster to be created. Defaults to""
.
- cert string
- The certificate for the SSL configuration.Conflicts with
ssl[0].leaf_domain_label
,ssl[0].overwrite_existing_domain
. Changing this forces a new Machine Learning Inference Cluster to be created. Defaults to""
. - cname string
- The cname of the SSL configuration.Conflicts with
ssl[0].leaf_domain_label
,ssl[0].overwrite_existing_domain
. Changing this forces a new Machine Learning Inference Cluster to be created. Defaults to""
. - key string
- The key content for the SSL configuration.Conflicts with
ssl[0].leaf_domain_label
,ssl[0].overwrite_existing_domain
. Changing this forces a new Machine Learning Inference Cluster to be created. Defaults to""
. - leaf
Domain stringLabel - The leaf domain label for the SSL configuration. Conflicts with
ssl[0].cert
,ssl[0].key
,ssl[0].cname
. Changing this forces a new Machine Learning Inference Cluster to be created. Defaults to""
. - overwrite
Existing booleanDomain - Whether or not to overwrite existing leaf domain. Conflicts with
ssl[0].cert
,ssl[0].key
,ssl[0].cname
Changing this forces a new Machine Learning Inference Cluster to be created. Defaults to""
.
- cert str
- The certificate for the SSL configuration.Conflicts with
ssl[0].leaf_domain_label
,ssl[0].overwrite_existing_domain
. Changing this forces a new Machine Learning Inference Cluster to be created. Defaults to""
. - cname str
- The cname of the SSL configuration.Conflicts with
ssl[0].leaf_domain_label
,ssl[0].overwrite_existing_domain
. Changing this forces a new Machine Learning Inference Cluster to be created. Defaults to""
. - key str
- The key content for the SSL configuration.Conflicts with
ssl[0].leaf_domain_label
,ssl[0].overwrite_existing_domain
. Changing this forces a new Machine Learning Inference Cluster to be created. Defaults to""
. - leaf_
domain_ strlabel - The leaf domain label for the SSL configuration. Conflicts with
ssl[0].cert
,ssl[0].key
,ssl[0].cname
. Changing this forces a new Machine Learning Inference Cluster to be created. Defaults to""
. - overwrite_
existing_ booldomain - Whether or not to overwrite existing leaf domain. Conflicts with
ssl[0].cert
,ssl[0].key
,ssl[0].cname
Changing this forces a new Machine Learning Inference Cluster to be created. Defaults to""
.
- cert String
- The certificate for the SSL configuration.Conflicts with
ssl[0].leaf_domain_label
,ssl[0].overwrite_existing_domain
. Changing this forces a new Machine Learning Inference Cluster to be created. Defaults to""
. - cname String
- The cname of the SSL configuration.Conflicts with
ssl[0].leaf_domain_label
,ssl[0].overwrite_existing_domain
. Changing this forces a new Machine Learning Inference Cluster to be created. Defaults to""
. - key String
- The key content for the SSL configuration.Conflicts with
ssl[0].leaf_domain_label
,ssl[0].overwrite_existing_domain
. Changing this forces a new Machine Learning Inference Cluster to be created. Defaults to""
. - leaf
Domain StringLabel - The leaf domain label for the SSL configuration. Conflicts with
ssl[0].cert
,ssl[0].key
,ssl[0].cname
. Changing this forces a new Machine Learning Inference Cluster to be created. Defaults to""
. - overwrite
Existing BooleanDomain - Whether or not to overwrite existing leaf domain. Conflicts with
ssl[0].cert
,ssl[0].key
,ssl[0].cname
Changing this forces a new Machine Learning Inference Cluster to be created. Defaults to""
.
Import
Machine Learning Inference Clusters can be imported using the resource id
, e.g.
$ pulumi import azure:machinelearning/inferenceCluster:InferenceCluster example /subscriptions/00000000-0000-0000-0000-000000000000/resourceGroups/resGroup1/providers/Microsoft.MachineLearningServices/workspaces/workspace1/computes/cluster1
To learn more about importing existing cloud resources, see Importing resources.
Package Details
- Repository
- Azure Classic pulumi/pulumi-azure
- License
- Apache-2.0
- Notes
- This Pulumi package is based on the
azurerm
Terraform Provider.