Inference Cluster Args
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());
}
}
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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
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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)