InferenceClusterArgs

data class InferenceClusterArgs(val clusterPurpose: Output<String>? = null, val description: Output<String>? = null, val identity: Output<InferenceClusterIdentityArgs>? = null, val kubernetesClusterId: Output<String>? = null, val location: Output<String>? = null, val machineLearningWorkspaceId: Output<String>? = null, val name: Output<String>? = null, val ssl: Output<InferenceClusterSslArgs>? = null, val tags: Output<Map<String, String>>? = null) : ConvertibleToJava<InferenceClusterArgs>

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

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 exampleResourceGroup = new ResourceGroup("exampleResourceGroup", ResourceGroupArgs.builder()
.location("west europe")
.tags(Map.of("stage", "example"))
.build());
var exampleInsights = new Insights("exampleInsights", InsightsArgs.builder()
.location(exampleResourceGroup.location())
.resourceGroupName(exampleResourceGroup.name())
.applicationType("web")
.build());
var exampleKeyVault = new KeyVault("exampleKeyVault", KeyVaultArgs.builder()
.location(exampleResourceGroup.location())
.resourceGroupName(exampleResourceGroup.name())
.tenantId(current.applyValue(getClientConfigResult -> getClientConfigResult.tenantId()))
.skuName("standard")
.purgeProtectionEnabled(true)
.build());
var exampleAccount = new Account("exampleAccount", AccountArgs.builder()
.location(exampleResourceGroup.location())
.resourceGroupName(exampleResourceGroup.name())
.accountTier("Standard")
.accountReplicationType("LRS")
.build());
var exampleWorkspace = new Workspace("exampleWorkspace", WorkspaceArgs.builder()
.location(exampleResourceGroup.location())
.resourceGroupName(exampleResourceGroup.name())
.applicationInsightsId(exampleInsights.id())
.keyVaultId(exampleKeyVault.id())
.storageAccountId(exampleAccount.id())
.identity(WorkspaceIdentityArgs.builder()
.type("SystemAssigned")
.build())
.build());
var exampleVirtualNetwork = new VirtualNetwork("exampleVirtualNetwork", VirtualNetworkArgs.builder()
.addressSpaces("10.1.0.0/16")
.location(exampleResourceGroup.location())
.resourceGroupName(exampleResourceGroup.name())
.build());
var exampleSubnet = new Subnet("exampleSubnet", SubnetArgs.builder()
.resourceGroupName(exampleResourceGroup.name())
.virtualNetworkName(exampleVirtualNetwork.name())
.addressPrefixes("10.1.0.0/24")
.build());
var exampleKubernetesCluster = new KubernetesCluster("exampleKubernetesCluster", KubernetesClusterArgs.builder()
.location(exampleResourceGroup.location())
.resourceGroupName(exampleResourceGroup.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()
.location(exampleResourceGroup.location())
.clusterPurpose("FastProd")
.kubernetesClusterId(exampleKubernetesCluster.id())
.description("This is an example cluster used with Terraform")
.machineLearningWorkspaceId(exampleWorkspace.id())
.tags(Map.of("stage", "example"))
.build());
}
}

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

Constructors

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fun InferenceClusterArgs(clusterPurpose: Output<String>? = null, description: Output<String>? = null, identity: Output<InferenceClusterIdentityArgs>? = null, kubernetesClusterId: Output<String>? = null, location: Output<String>? = null, machineLearningWorkspaceId: Output<String>? = null, name: Output<String>? = null, ssl: Output<InferenceClusterSslArgs>? = null, tags: Output<Map<String, String>>? = null)

Functions

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open override fun toJava(): InferenceClusterArgs

Properties

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val clusterPurpose: Output<String>? = null

The purpose of the Inference Cluster. Options are DevTest, DenseProd and FastProd. If used for Development or Testing, use DevTest here. Default purpose is FastProd, which is recommended for production workloads. Changing this forces a new Machine Learning Inference Cluster to be created.

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val description: Output<String>? = null

The description of the Machine Learning Inference Cluster. Changing this forces a new Machine Learning Inference Cluster to be created.

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An identity block as defined below. Changing this forces a new Machine Learning Inference Cluster to be created.

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val kubernetesClusterId: Output<String>? = null

The ID of the Kubernetes Cluster. Changing this forces a new Machine Learning Inference Cluster to be created.

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val location: Output<String>? = null

The Azure Region where the Machine Learning Inference Cluster should exist. Changing this forces a new Machine Learning Inference Cluster to be created.

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val machineLearningWorkspaceId: Output<String>? = null

The ID of the Machine Learning Workspace. Changing this forces a new Machine Learning Inference Cluster to be created.

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val name: Output<String>? = null

The name which should be used for this Machine Learning Inference Cluster. Changing this forces a new Machine Learning Inference Cluster to be created.

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val ssl: Output<InferenceClusterSslArgs>? = null

A ssl block as defined below. Changing this forces a new Machine Learning Inference Cluster to be created.

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val tags: Output<Map<String, String>>? = null

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.