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Oracle Cloud Infrastructure v1.41.0 published on Wednesday, Jun 19, 2024 by Pulumi

oci.DataScience.ModelDeployment

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Oracle Cloud Infrastructure v1.41.0 published on Wednesday, Jun 19, 2024 by Pulumi

    This resource provides the Model Deployment resource in Oracle Cloud Infrastructure Datascience service.

    Creates a new model deployment.

    Example Usage

    import * as pulumi from "@pulumi/pulumi";
    import * as oci from "@pulumi/oci";
    
    const testModelDeployment = new oci.datascience.ModelDeployment("test_model_deployment", {
        compartmentId: compartmentId,
        modelDeploymentConfigurationDetails: {
            deploymentType: modelDeploymentModelDeploymentConfigurationDetailsDeploymentType,
            modelConfigurationDetails: {
                instanceConfiguration: {
                    instanceShapeName: testShape.name,
                    modelDeploymentInstanceShapeConfigDetails: {
                        cpuBaseline: modelDeploymentModelDeploymentConfigurationDetailsModelConfigurationDetailsInstanceConfigurationModelDeploymentInstanceShapeConfigDetailsCpuBaseline,
                        memoryInGbs: modelDeploymentModelDeploymentConfigurationDetailsModelConfigurationDetailsInstanceConfigurationModelDeploymentInstanceShapeConfigDetailsMemoryInGbs,
                        ocpus: modelDeploymentModelDeploymentConfigurationDetailsModelConfigurationDetailsInstanceConfigurationModelDeploymentInstanceShapeConfigDetailsOcpus,
                    },
                    subnetId: testSubnet.id,
                },
                modelId: testModel.id,
                bandwidthMbps: modelDeploymentModelDeploymentConfigurationDetailsModelConfigurationDetailsBandwidthMbps,
                maximumBandwidthMbps: modelDeploymentModelDeploymentConfigurationDetailsModelConfigurationDetailsMaximumBandwidthMbps,
                scalingPolicy: {
                    policyType: modelDeploymentModelDeploymentConfigurationDetailsModelConfigurationDetailsScalingPolicyPolicyType,
                    autoScalingPolicies: [{
                        autoScalingPolicyType: modelDeploymentModelDeploymentConfigurationDetailsModelConfigurationDetailsScalingPolicyAutoScalingPoliciesAutoScalingPolicyType,
                        initialInstanceCount: modelDeploymentModelDeploymentConfigurationDetailsModelConfigurationDetailsScalingPolicyAutoScalingPoliciesInitialInstanceCount,
                        maximumInstanceCount: modelDeploymentModelDeploymentConfigurationDetailsModelConfigurationDetailsScalingPolicyAutoScalingPoliciesMaximumInstanceCount,
                        minimumInstanceCount: modelDeploymentModelDeploymentConfigurationDetailsModelConfigurationDetailsScalingPolicyAutoScalingPoliciesMinimumInstanceCount,
                        rules: [{
                            metricExpressionRuleType: modelDeploymentModelDeploymentConfigurationDetailsModelConfigurationDetailsScalingPolicyAutoScalingPoliciesRulesMetricExpressionRuleType,
                            scaleInConfiguration: {
                                instanceCountAdjustment: modelDeploymentModelDeploymentConfigurationDetailsModelConfigurationDetailsScalingPolicyAutoScalingPoliciesRulesScaleInConfigurationInstanceCountAdjustment,
                                pendingDuration: modelDeploymentModelDeploymentConfigurationDetailsModelConfigurationDetailsScalingPolicyAutoScalingPoliciesRulesScaleInConfigurationPendingDuration,
                                query: modelDeploymentModelDeploymentConfigurationDetailsModelConfigurationDetailsScalingPolicyAutoScalingPoliciesRulesScaleInConfigurationQuery,
                                scalingConfigurationType: modelDeploymentModelDeploymentConfigurationDetailsModelConfigurationDetailsScalingPolicyAutoScalingPoliciesRulesScaleInConfigurationScalingConfigurationType,
                                threshold: modelDeploymentModelDeploymentConfigurationDetailsModelConfigurationDetailsScalingPolicyAutoScalingPoliciesRulesScaleInConfigurationThreshold,
                            },
                            scaleOutConfiguration: {
                                instanceCountAdjustment: modelDeploymentModelDeploymentConfigurationDetailsModelConfigurationDetailsScalingPolicyAutoScalingPoliciesRulesScaleOutConfigurationInstanceCountAdjustment,
                                pendingDuration: modelDeploymentModelDeploymentConfigurationDetailsModelConfigurationDetailsScalingPolicyAutoScalingPoliciesRulesScaleOutConfigurationPendingDuration,
                                query: modelDeploymentModelDeploymentConfigurationDetailsModelConfigurationDetailsScalingPolicyAutoScalingPoliciesRulesScaleOutConfigurationQuery,
                                scalingConfigurationType: modelDeploymentModelDeploymentConfigurationDetailsModelConfigurationDetailsScalingPolicyAutoScalingPoliciesRulesScaleOutConfigurationScalingConfigurationType,
                                threshold: modelDeploymentModelDeploymentConfigurationDetailsModelConfigurationDetailsScalingPolicyAutoScalingPoliciesRulesScaleOutConfigurationThreshold,
                            },
                            metricType: modelDeploymentModelDeploymentConfigurationDetailsModelConfigurationDetailsScalingPolicyAutoScalingPoliciesRulesMetricType,
                        }],
                    }],
                    coolDownInSeconds: modelDeploymentModelDeploymentConfigurationDetailsModelConfigurationDetailsScalingPolicyCoolDownInSeconds,
                    instanceCount: modelDeploymentModelDeploymentConfigurationDetailsModelConfigurationDetailsScalingPolicyInstanceCount,
                    isEnabled: modelDeploymentModelDeploymentConfigurationDetailsModelConfigurationDetailsScalingPolicyIsEnabled,
                },
            },
            environmentConfigurationDetails: {
                environmentConfigurationType: modelDeploymentModelDeploymentConfigurationDetailsEnvironmentConfigurationDetailsEnvironmentConfigurationType,
                cmds: modelDeploymentModelDeploymentConfigurationDetailsEnvironmentConfigurationDetailsCmd,
                entrypoints: modelDeploymentModelDeploymentConfigurationDetailsEnvironmentConfigurationDetailsEntrypoint,
                environmentVariables: modelDeploymentModelDeploymentConfigurationDetailsEnvironmentConfigurationDetailsEnvironmentVariables,
                healthCheckPort: modelDeploymentModelDeploymentConfigurationDetailsEnvironmentConfigurationDetailsHealthCheckPort,
                image: modelDeploymentModelDeploymentConfigurationDetailsEnvironmentConfigurationDetailsImage,
                imageDigest: modelDeploymentModelDeploymentConfigurationDetailsEnvironmentConfigurationDetailsImageDigest,
                serverPort: modelDeploymentModelDeploymentConfigurationDetailsEnvironmentConfigurationDetailsServerPort,
            },
        },
        projectId: testProject.id,
        categoryLogDetails: {
            access: {
                logGroupId: testLogGroup.id,
                logId: testLog.id,
            },
            predict: {
                logGroupId: testLogGroup.id,
                logId: testLog.id,
            },
        },
        definedTags: {
            "Operations.CostCenter": "42",
        },
        description: modelDeploymentDescription,
        displayName: modelDeploymentDisplayName,
        freeformTags: {
            Department: "Finance",
        },
        opcParentRptUrl: modelDeploymentOpcParentRptUrl,
    });
    
    import pulumi
    import pulumi_oci as oci
    
    test_model_deployment = oci.data_science.ModelDeployment("test_model_deployment",
        compartment_id=compartment_id,
        model_deployment_configuration_details=oci.data_science.ModelDeploymentModelDeploymentConfigurationDetailsArgs(
            deployment_type=model_deployment_model_deployment_configuration_details_deployment_type,
            model_configuration_details=oci.data_science.ModelDeploymentModelDeploymentConfigurationDetailsModelConfigurationDetailsArgs(
                instance_configuration=oci.data_science.ModelDeploymentModelDeploymentConfigurationDetailsModelConfigurationDetailsInstanceConfigurationArgs(
                    instance_shape_name=test_shape["name"],
                    model_deployment_instance_shape_config_details=oci.data_science.ModelDeploymentModelDeploymentConfigurationDetailsModelConfigurationDetailsInstanceConfigurationModelDeploymentInstanceShapeConfigDetailsArgs(
                        cpu_baseline=model_deployment_model_deployment_configuration_details_model_configuration_details_instance_configuration_model_deployment_instance_shape_config_details_cpu_baseline,
                        memory_in_gbs=model_deployment_model_deployment_configuration_details_model_configuration_details_instance_configuration_model_deployment_instance_shape_config_details_memory_in_gbs,
                        ocpus=model_deployment_model_deployment_configuration_details_model_configuration_details_instance_configuration_model_deployment_instance_shape_config_details_ocpus,
                    ),
                    subnet_id=test_subnet["id"],
                ),
                model_id=test_model["id"],
                bandwidth_mbps=model_deployment_model_deployment_configuration_details_model_configuration_details_bandwidth_mbps,
                maximum_bandwidth_mbps=model_deployment_model_deployment_configuration_details_model_configuration_details_maximum_bandwidth_mbps,
                scaling_policy=oci.data_science.ModelDeploymentModelDeploymentConfigurationDetailsModelConfigurationDetailsScalingPolicyArgs(
                    policy_type=model_deployment_model_deployment_configuration_details_model_configuration_details_scaling_policy_policy_type,
                    auto_scaling_policies=[oci.data_science.ModelDeploymentModelDeploymentConfigurationDetailsModelConfigurationDetailsScalingPolicyAutoScalingPolicyArgs(
                        auto_scaling_policy_type=model_deployment_model_deployment_configuration_details_model_configuration_details_scaling_policy_auto_scaling_policies_auto_scaling_policy_type,
                        initial_instance_count=model_deployment_model_deployment_configuration_details_model_configuration_details_scaling_policy_auto_scaling_policies_initial_instance_count,
                        maximum_instance_count=model_deployment_model_deployment_configuration_details_model_configuration_details_scaling_policy_auto_scaling_policies_maximum_instance_count,
                        minimum_instance_count=model_deployment_model_deployment_configuration_details_model_configuration_details_scaling_policy_auto_scaling_policies_minimum_instance_count,
                        rules=[oci.data_science.ModelDeploymentModelDeploymentConfigurationDetailsModelConfigurationDetailsScalingPolicyAutoScalingPolicyRuleArgs(
                            metric_expression_rule_type=model_deployment_model_deployment_configuration_details_model_configuration_details_scaling_policy_auto_scaling_policies_rules_metric_expression_rule_type,
                            scale_in_configuration=oci.data_science.ModelDeploymentModelDeploymentConfigurationDetailsModelConfigurationDetailsScalingPolicyAutoScalingPolicyRuleScaleInConfigurationArgs(
                                instance_count_adjustment=model_deployment_model_deployment_configuration_details_model_configuration_details_scaling_policy_auto_scaling_policies_rules_scale_in_configuration_instance_count_adjustment,
                                pending_duration=model_deployment_model_deployment_configuration_details_model_configuration_details_scaling_policy_auto_scaling_policies_rules_scale_in_configuration_pending_duration,
                                query=model_deployment_model_deployment_configuration_details_model_configuration_details_scaling_policy_auto_scaling_policies_rules_scale_in_configuration_query,
                                scaling_configuration_type=model_deployment_model_deployment_configuration_details_model_configuration_details_scaling_policy_auto_scaling_policies_rules_scale_in_configuration_scaling_configuration_type,
                                threshold=model_deployment_model_deployment_configuration_details_model_configuration_details_scaling_policy_auto_scaling_policies_rules_scale_in_configuration_threshold,
                            ),
                            scale_out_configuration=oci.data_science.ModelDeploymentModelDeploymentConfigurationDetailsModelConfigurationDetailsScalingPolicyAutoScalingPolicyRuleScaleOutConfigurationArgs(
                                instance_count_adjustment=model_deployment_model_deployment_configuration_details_model_configuration_details_scaling_policy_auto_scaling_policies_rules_scale_out_configuration_instance_count_adjustment,
                                pending_duration=model_deployment_model_deployment_configuration_details_model_configuration_details_scaling_policy_auto_scaling_policies_rules_scale_out_configuration_pending_duration,
                                query=model_deployment_model_deployment_configuration_details_model_configuration_details_scaling_policy_auto_scaling_policies_rules_scale_out_configuration_query,
                                scaling_configuration_type=model_deployment_model_deployment_configuration_details_model_configuration_details_scaling_policy_auto_scaling_policies_rules_scale_out_configuration_scaling_configuration_type,
                                threshold=model_deployment_model_deployment_configuration_details_model_configuration_details_scaling_policy_auto_scaling_policies_rules_scale_out_configuration_threshold,
                            ),
                            metric_type=model_deployment_model_deployment_configuration_details_model_configuration_details_scaling_policy_auto_scaling_policies_rules_metric_type,
                        )],
                    )],
                    cool_down_in_seconds=model_deployment_model_deployment_configuration_details_model_configuration_details_scaling_policy_cool_down_in_seconds,
                    instance_count=model_deployment_model_deployment_configuration_details_model_configuration_details_scaling_policy_instance_count,
                    is_enabled=model_deployment_model_deployment_configuration_details_model_configuration_details_scaling_policy_is_enabled,
                ),
            ),
            environment_configuration_details=oci.data_science.ModelDeploymentModelDeploymentConfigurationDetailsEnvironmentConfigurationDetailsArgs(
                environment_configuration_type=model_deployment_model_deployment_configuration_details_environment_configuration_details_environment_configuration_type,
                cmds=model_deployment_model_deployment_configuration_details_environment_configuration_details_cmd,
                entrypoints=model_deployment_model_deployment_configuration_details_environment_configuration_details_entrypoint,
                environment_variables=model_deployment_model_deployment_configuration_details_environment_configuration_details_environment_variables,
                health_check_port=model_deployment_model_deployment_configuration_details_environment_configuration_details_health_check_port,
                image=model_deployment_model_deployment_configuration_details_environment_configuration_details_image,
                image_digest=model_deployment_model_deployment_configuration_details_environment_configuration_details_image_digest,
                server_port=model_deployment_model_deployment_configuration_details_environment_configuration_details_server_port,
            ),
        ),
        project_id=test_project["id"],
        category_log_details=oci.data_science.ModelDeploymentCategoryLogDetailsArgs(
            access=oci.data_science.ModelDeploymentCategoryLogDetailsAccessArgs(
                log_group_id=test_log_group["id"],
                log_id=test_log["id"],
            ),
            predict=oci.data_science.ModelDeploymentCategoryLogDetailsPredictArgs(
                log_group_id=test_log_group["id"],
                log_id=test_log["id"],
            ),
        ),
        defined_tags={
            "Operations.CostCenter": "42",
        },
        description=model_deployment_description,
        display_name=model_deployment_display_name,
        freeform_tags={
            "Department": "Finance",
        },
        opc_parent_rpt_url=model_deployment_opc_parent_rpt_url)
    
    package main
    
    import (
    	"github.com/pulumi/pulumi-oci/sdk/go/oci/DataScience"
    	"github.com/pulumi/pulumi/sdk/v3/go/pulumi"
    )
    
    func main() {
    	pulumi.Run(func(ctx *pulumi.Context) error {
    		_, err := DataScience.NewModelDeployment(ctx, "test_model_deployment", &DataScience.ModelDeploymentArgs{
    			CompartmentId: pulumi.Any(compartmentId),
    			ModelDeploymentConfigurationDetails: &datascience.ModelDeploymentModelDeploymentConfigurationDetailsArgs{
    				DeploymentType: pulumi.Any(modelDeploymentModelDeploymentConfigurationDetailsDeploymentType),
    				ModelConfigurationDetails: &datascience.ModelDeploymentModelDeploymentConfigurationDetailsModelConfigurationDetailsArgs{
    					InstanceConfiguration: &datascience.ModelDeploymentModelDeploymentConfigurationDetailsModelConfigurationDetailsInstanceConfigurationArgs{
    						InstanceShapeName: pulumi.Any(testShape.Name),
    						ModelDeploymentInstanceShapeConfigDetails: &datascience.ModelDeploymentModelDeploymentConfigurationDetailsModelConfigurationDetailsInstanceConfigurationModelDeploymentInstanceShapeConfigDetailsArgs{
    							CpuBaseline: pulumi.Any(modelDeploymentModelDeploymentConfigurationDetailsModelConfigurationDetailsInstanceConfigurationModelDeploymentInstanceShapeConfigDetailsCpuBaseline),
    							MemoryInGbs: pulumi.Any(modelDeploymentModelDeploymentConfigurationDetailsModelConfigurationDetailsInstanceConfigurationModelDeploymentInstanceShapeConfigDetailsMemoryInGbs),
    							Ocpus:       pulumi.Any(modelDeploymentModelDeploymentConfigurationDetailsModelConfigurationDetailsInstanceConfigurationModelDeploymentInstanceShapeConfigDetailsOcpus),
    						},
    						SubnetId: pulumi.Any(testSubnet.Id),
    					},
    					ModelId:              pulumi.Any(testModel.Id),
    					BandwidthMbps:        pulumi.Any(modelDeploymentModelDeploymentConfigurationDetailsModelConfigurationDetailsBandwidthMbps),
    					MaximumBandwidthMbps: pulumi.Any(modelDeploymentModelDeploymentConfigurationDetailsModelConfigurationDetailsMaximumBandwidthMbps),
    					ScalingPolicy: &datascience.ModelDeploymentModelDeploymentConfigurationDetailsModelConfigurationDetailsScalingPolicyArgs{
    						PolicyType: pulumi.Any(modelDeploymentModelDeploymentConfigurationDetailsModelConfigurationDetailsScalingPolicyPolicyType),
    						AutoScalingPolicies: datascience.ModelDeploymentModelDeploymentConfigurationDetailsModelConfigurationDetailsScalingPolicyAutoScalingPolicyArray{
    							&datascience.ModelDeploymentModelDeploymentConfigurationDetailsModelConfigurationDetailsScalingPolicyAutoScalingPolicyArgs{
    								AutoScalingPolicyType: pulumi.Any(modelDeploymentModelDeploymentConfigurationDetailsModelConfigurationDetailsScalingPolicyAutoScalingPoliciesAutoScalingPolicyType),
    								InitialInstanceCount:  pulumi.Any(modelDeploymentModelDeploymentConfigurationDetailsModelConfigurationDetailsScalingPolicyAutoScalingPoliciesInitialInstanceCount),
    								MaximumInstanceCount:  pulumi.Any(modelDeploymentModelDeploymentConfigurationDetailsModelConfigurationDetailsScalingPolicyAutoScalingPoliciesMaximumInstanceCount),
    								MinimumInstanceCount:  pulumi.Any(modelDeploymentModelDeploymentConfigurationDetailsModelConfigurationDetailsScalingPolicyAutoScalingPoliciesMinimumInstanceCount),
    								Rules: datascience.ModelDeploymentModelDeploymentConfigurationDetailsModelConfigurationDetailsScalingPolicyAutoScalingPolicyRuleArray{
    									&datascience.ModelDeploymentModelDeploymentConfigurationDetailsModelConfigurationDetailsScalingPolicyAutoScalingPolicyRuleArgs{
    										MetricExpressionRuleType: pulumi.Any(modelDeploymentModelDeploymentConfigurationDetailsModelConfigurationDetailsScalingPolicyAutoScalingPoliciesRulesMetricExpressionRuleType),
    										ScaleInConfiguration: &datascience.ModelDeploymentModelDeploymentConfigurationDetailsModelConfigurationDetailsScalingPolicyAutoScalingPolicyRuleScaleInConfigurationArgs{
    											InstanceCountAdjustment:  pulumi.Any(modelDeploymentModelDeploymentConfigurationDetailsModelConfigurationDetailsScalingPolicyAutoScalingPoliciesRulesScaleInConfigurationInstanceCountAdjustment),
    											PendingDuration:          pulumi.Any(modelDeploymentModelDeploymentConfigurationDetailsModelConfigurationDetailsScalingPolicyAutoScalingPoliciesRulesScaleInConfigurationPendingDuration),
    											Query:                    pulumi.Any(modelDeploymentModelDeploymentConfigurationDetailsModelConfigurationDetailsScalingPolicyAutoScalingPoliciesRulesScaleInConfigurationQuery),
    											ScalingConfigurationType: pulumi.Any(modelDeploymentModelDeploymentConfigurationDetailsModelConfigurationDetailsScalingPolicyAutoScalingPoliciesRulesScaleInConfigurationScalingConfigurationType),
    											Threshold:                pulumi.Any(modelDeploymentModelDeploymentConfigurationDetailsModelConfigurationDetailsScalingPolicyAutoScalingPoliciesRulesScaleInConfigurationThreshold),
    										},
    										ScaleOutConfiguration: &datascience.ModelDeploymentModelDeploymentConfigurationDetailsModelConfigurationDetailsScalingPolicyAutoScalingPolicyRuleScaleOutConfigurationArgs{
    											InstanceCountAdjustment:  pulumi.Any(modelDeploymentModelDeploymentConfigurationDetailsModelConfigurationDetailsScalingPolicyAutoScalingPoliciesRulesScaleOutConfigurationInstanceCountAdjustment),
    											PendingDuration:          pulumi.Any(modelDeploymentModelDeploymentConfigurationDetailsModelConfigurationDetailsScalingPolicyAutoScalingPoliciesRulesScaleOutConfigurationPendingDuration),
    											Query:                    pulumi.Any(modelDeploymentModelDeploymentConfigurationDetailsModelConfigurationDetailsScalingPolicyAutoScalingPoliciesRulesScaleOutConfigurationQuery),
    											ScalingConfigurationType: pulumi.Any(modelDeploymentModelDeploymentConfigurationDetailsModelConfigurationDetailsScalingPolicyAutoScalingPoliciesRulesScaleOutConfigurationScalingConfigurationType),
    											Threshold:                pulumi.Any(modelDeploymentModelDeploymentConfigurationDetailsModelConfigurationDetailsScalingPolicyAutoScalingPoliciesRulesScaleOutConfigurationThreshold),
    										},
    										MetricType: pulumi.Any(modelDeploymentModelDeploymentConfigurationDetailsModelConfigurationDetailsScalingPolicyAutoScalingPoliciesRulesMetricType),
    									},
    								},
    							},
    						},
    						CoolDownInSeconds: pulumi.Any(modelDeploymentModelDeploymentConfigurationDetailsModelConfigurationDetailsScalingPolicyCoolDownInSeconds),
    						InstanceCount:     pulumi.Any(modelDeploymentModelDeploymentConfigurationDetailsModelConfigurationDetailsScalingPolicyInstanceCount),
    						IsEnabled:         pulumi.Any(modelDeploymentModelDeploymentConfigurationDetailsModelConfigurationDetailsScalingPolicyIsEnabled),
    					},
    				},
    				EnvironmentConfigurationDetails: &datascience.ModelDeploymentModelDeploymentConfigurationDetailsEnvironmentConfigurationDetailsArgs{
    					EnvironmentConfigurationType: pulumi.Any(modelDeploymentModelDeploymentConfigurationDetailsEnvironmentConfigurationDetailsEnvironmentConfigurationType),
    					Cmds:                         pulumi.Any(modelDeploymentModelDeploymentConfigurationDetailsEnvironmentConfigurationDetailsCmd),
    					Entrypoints:                  pulumi.Any(modelDeploymentModelDeploymentConfigurationDetailsEnvironmentConfigurationDetailsEntrypoint),
    					EnvironmentVariables:         pulumi.Any(modelDeploymentModelDeploymentConfigurationDetailsEnvironmentConfigurationDetailsEnvironmentVariables),
    					HealthCheckPort:              pulumi.Any(modelDeploymentModelDeploymentConfigurationDetailsEnvironmentConfigurationDetailsHealthCheckPort),
    					Image:                        pulumi.Any(modelDeploymentModelDeploymentConfigurationDetailsEnvironmentConfigurationDetailsImage),
    					ImageDigest:                  pulumi.Any(modelDeploymentModelDeploymentConfigurationDetailsEnvironmentConfigurationDetailsImageDigest),
    					ServerPort:                   pulumi.Any(modelDeploymentModelDeploymentConfigurationDetailsEnvironmentConfigurationDetailsServerPort),
    				},
    			},
    			ProjectId: pulumi.Any(testProject.Id),
    			CategoryLogDetails: &datascience.ModelDeploymentCategoryLogDetailsArgs{
    				Access: &datascience.ModelDeploymentCategoryLogDetailsAccessArgs{
    					LogGroupId: pulumi.Any(testLogGroup.Id),
    					LogId:      pulumi.Any(testLog.Id),
    				},
    				Predict: &datascience.ModelDeploymentCategoryLogDetailsPredictArgs{
    					LogGroupId: pulumi.Any(testLogGroup.Id),
    					LogId:      pulumi.Any(testLog.Id),
    				},
    			},
    			DefinedTags: pulumi.Map{
    				"Operations.CostCenter": pulumi.Any("42"),
    			},
    			Description: pulumi.Any(modelDeploymentDescription),
    			DisplayName: pulumi.Any(modelDeploymentDisplayName),
    			FreeformTags: pulumi.Map{
    				"Department": pulumi.Any("Finance"),
    			},
    			OpcParentRptUrl: pulumi.Any(modelDeploymentOpcParentRptUrl),
    		})
    		if err != nil {
    			return err
    		}
    		return nil
    	})
    }
    
    using System.Collections.Generic;
    using System.Linq;
    using Pulumi;
    using Oci = Pulumi.Oci;
    
    return await Deployment.RunAsync(() => 
    {
        var testModelDeployment = new Oci.DataScience.ModelDeployment("test_model_deployment", new()
        {
            CompartmentId = compartmentId,
            ModelDeploymentConfigurationDetails = new Oci.DataScience.Inputs.ModelDeploymentModelDeploymentConfigurationDetailsArgs
            {
                DeploymentType = modelDeploymentModelDeploymentConfigurationDetailsDeploymentType,
                ModelConfigurationDetails = new Oci.DataScience.Inputs.ModelDeploymentModelDeploymentConfigurationDetailsModelConfigurationDetailsArgs
                {
                    InstanceConfiguration = new Oci.DataScience.Inputs.ModelDeploymentModelDeploymentConfigurationDetailsModelConfigurationDetailsInstanceConfigurationArgs
                    {
                        InstanceShapeName = testShape.Name,
                        ModelDeploymentInstanceShapeConfigDetails = new Oci.DataScience.Inputs.ModelDeploymentModelDeploymentConfigurationDetailsModelConfigurationDetailsInstanceConfigurationModelDeploymentInstanceShapeConfigDetailsArgs
                        {
                            CpuBaseline = modelDeploymentModelDeploymentConfigurationDetailsModelConfigurationDetailsInstanceConfigurationModelDeploymentInstanceShapeConfigDetailsCpuBaseline,
                            MemoryInGbs = modelDeploymentModelDeploymentConfigurationDetailsModelConfigurationDetailsInstanceConfigurationModelDeploymentInstanceShapeConfigDetailsMemoryInGbs,
                            Ocpus = modelDeploymentModelDeploymentConfigurationDetailsModelConfigurationDetailsInstanceConfigurationModelDeploymentInstanceShapeConfigDetailsOcpus,
                        },
                        SubnetId = testSubnet.Id,
                    },
                    ModelId = testModel.Id,
                    BandwidthMbps = modelDeploymentModelDeploymentConfigurationDetailsModelConfigurationDetailsBandwidthMbps,
                    MaximumBandwidthMbps = modelDeploymentModelDeploymentConfigurationDetailsModelConfigurationDetailsMaximumBandwidthMbps,
                    ScalingPolicy = new Oci.DataScience.Inputs.ModelDeploymentModelDeploymentConfigurationDetailsModelConfigurationDetailsScalingPolicyArgs
                    {
                        PolicyType = modelDeploymentModelDeploymentConfigurationDetailsModelConfigurationDetailsScalingPolicyPolicyType,
                        AutoScalingPolicies = new[]
                        {
                            new Oci.DataScience.Inputs.ModelDeploymentModelDeploymentConfigurationDetailsModelConfigurationDetailsScalingPolicyAutoScalingPolicyArgs
                            {
                                AutoScalingPolicyType = modelDeploymentModelDeploymentConfigurationDetailsModelConfigurationDetailsScalingPolicyAutoScalingPoliciesAutoScalingPolicyType,
                                InitialInstanceCount = modelDeploymentModelDeploymentConfigurationDetailsModelConfigurationDetailsScalingPolicyAutoScalingPoliciesInitialInstanceCount,
                                MaximumInstanceCount = modelDeploymentModelDeploymentConfigurationDetailsModelConfigurationDetailsScalingPolicyAutoScalingPoliciesMaximumInstanceCount,
                                MinimumInstanceCount = modelDeploymentModelDeploymentConfigurationDetailsModelConfigurationDetailsScalingPolicyAutoScalingPoliciesMinimumInstanceCount,
                                Rules = new[]
                                {
                                    new Oci.DataScience.Inputs.ModelDeploymentModelDeploymentConfigurationDetailsModelConfigurationDetailsScalingPolicyAutoScalingPolicyRuleArgs
                                    {
                                        MetricExpressionRuleType = modelDeploymentModelDeploymentConfigurationDetailsModelConfigurationDetailsScalingPolicyAutoScalingPoliciesRulesMetricExpressionRuleType,
                                        ScaleInConfiguration = new Oci.DataScience.Inputs.ModelDeploymentModelDeploymentConfigurationDetailsModelConfigurationDetailsScalingPolicyAutoScalingPolicyRuleScaleInConfigurationArgs
                                        {
                                            InstanceCountAdjustment = modelDeploymentModelDeploymentConfigurationDetailsModelConfigurationDetailsScalingPolicyAutoScalingPoliciesRulesScaleInConfigurationInstanceCountAdjustment,
                                            PendingDuration = modelDeploymentModelDeploymentConfigurationDetailsModelConfigurationDetailsScalingPolicyAutoScalingPoliciesRulesScaleInConfigurationPendingDuration,
                                            Query = modelDeploymentModelDeploymentConfigurationDetailsModelConfigurationDetailsScalingPolicyAutoScalingPoliciesRulesScaleInConfigurationQuery,
                                            ScalingConfigurationType = modelDeploymentModelDeploymentConfigurationDetailsModelConfigurationDetailsScalingPolicyAutoScalingPoliciesRulesScaleInConfigurationScalingConfigurationType,
                                            Threshold = modelDeploymentModelDeploymentConfigurationDetailsModelConfigurationDetailsScalingPolicyAutoScalingPoliciesRulesScaleInConfigurationThreshold,
                                        },
                                        ScaleOutConfiguration = new Oci.DataScience.Inputs.ModelDeploymentModelDeploymentConfigurationDetailsModelConfigurationDetailsScalingPolicyAutoScalingPolicyRuleScaleOutConfigurationArgs
                                        {
                                            InstanceCountAdjustment = modelDeploymentModelDeploymentConfigurationDetailsModelConfigurationDetailsScalingPolicyAutoScalingPoliciesRulesScaleOutConfigurationInstanceCountAdjustment,
                                            PendingDuration = modelDeploymentModelDeploymentConfigurationDetailsModelConfigurationDetailsScalingPolicyAutoScalingPoliciesRulesScaleOutConfigurationPendingDuration,
                                            Query = modelDeploymentModelDeploymentConfigurationDetailsModelConfigurationDetailsScalingPolicyAutoScalingPoliciesRulesScaleOutConfigurationQuery,
                                            ScalingConfigurationType = modelDeploymentModelDeploymentConfigurationDetailsModelConfigurationDetailsScalingPolicyAutoScalingPoliciesRulesScaleOutConfigurationScalingConfigurationType,
                                            Threshold = modelDeploymentModelDeploymentConfigurationDetailsModelConfigurationDetailsScalingPolicyAutoScalingPoliciesRulesScaleOutConfigurationThreshold,
                                        },
                                        MetricType = modelDeploymentModelDeploymentConfigurationDetailsModelConfigurationDetailsScalingPolicyAutoScalingPoliciesRulesMetricType,
                                    },
                                },
                            },
                        },
                        CoolDownInSeconds = modelDeploymentModelDeploymentConfigurationDetailsModelConfigurationDetailsScalingPolicyCoolDownInSeconds,
                        InstanceCount = modelDeploymentModelDeploymentConfigurationDetailsModelConfigurationDetailsScalingPolicyInstanceCount,
                        IsEnabled = modelDeploymentModelDeploymentConfigurationDetailsModelConfigurationDetailsScalingPolicyIsEnabled,
                    },
                },
                EnvironmentConfigurationDetails = new Oci.DataScience.Inputs.ModelDeploymentModelDeploymentConfigurationDetailsEnvironmentConfigurationDetailsArgs
                {
                    EnvironmentConfigurationType = modelDeploymentModelDeploymentConfigurationDetailsEnvironmentConfigurationDetailsEnvironmentConfigurationType,
                    Cmds = modelDeploymentModelDeploymentConfigurationDetailsEnvironmentConfigurationDetailsCmd,
                    Entrypoints = modelDeploymentModelDeploymentConfigurationDetailsEnvironmentConfigurationDetailsEntrypoint,
                    EnvironmentVariables = modelDeploymentModelDeploymentConfigurationDetailsEnvironmentConfigurationDetailsEnvironmentVariables,
                    HealthCheckPort = modelDeploymentModelDeploymentConfigurationDetailsEnvironmentConfigurationDetailsHealthCheckPort,
                    Image = modelDeploymentModelDeploymentConfigurationDetailsEnvironmentConfigurationDetailsImage,
                    ImageDigest = modelDeploymentModelDeploymentConfigurationDetailsEnvironmentConfigurationDetailsImageDigest,
                    ServerPort = modelDeploymentModelDeploymentConfigurationDetailsEnvironmentConfigurationDetailsServerPort,
                },
            },
            ProjectId = testProject.Id,
            CategoryLogDetails = new Oci.DataScience.Inputs.ModelDeploymentCategoryLogDetailsArgs
            {
                Access = new Oci.DataScience.Inputs.ModelDeploymentCategoryLogDetailsAccessArgs
                {
                    LogGroupId = testLogGroup.Id,
                    LogId = testLog.Id,
                },
                Predict = new Oci.DataScience.Inputs.ModelDeploymentCategoryLogDetailsPredictArgs
                {
                    LogGroupId = testLogGroup.Id,
                    LogId = testLog.Id,
                },
            },
            DefinedTags = 
            {
                { "Operations.CostCenter", "42" },
            },
            Description = modelDeploymentDescription,
            DisplayName = modelDeploymentDisplayName,
            FreeformTags = 
            {
                { "Department", "Finance" },
            },
            OpcParentRptUrl = modelDeploymentOpcParentRptUrl,
        });
    
    });
    
    package generated_program;
    
    import com.pulumi.Context;
    import com.pulumi.Pulumi;
    import com.pulumi.core.Output;
    import com.pulumi.oci.DataScience.ModelDeployment;
    import com.pulumi.oci.DataScience.ModelDeploymentArgs;
    import com.pulumi.oci.DataScience.inputs.ModelDeploymentModelDeploymentConfigurationDetailsArgs;
    import com.pulumi.oci.DataScience.inputs.ModelDeploymentModelDeploymentConfigurationDetailsModelConfigurationDetailsArgs;
    import com.pulumi.oci.DataScience.inputs.ModelDeploymentModelDeploymentConfigurationDetailsModelConfigurationDetailsInstanceConfigurationArgs;
    import com.pulumi.oci.DataScience.inputs.ModelDeploymentModelDeploymentConfigurationDetailsModelConfigurationDetailsInstanceConfigurationModelDeploymentInstanceShapeConfigDetailsArgs;
    import com.pulumi.oci.DataScience.inputs.ModelDeploymentModelDeploymentConfigurationDetailsModelConfigurationDetailsScalingPolicyArgs;
    import com.pulumi.oci.DataScience.inputs.ModelDeploymentModelDeploymentConfigurationDetailsEnvironmentConfigurationDetailsArgs;
    import com.pulumi.oci.DataScience.inputs.ModelDeploymentCategoryLogDetailsArgs;
    import com.pulumi.oci.DataScience.inputs.ModelDeploymentCategoryLogDetailsAccessArgs;
    import com.pulumi.oci.DataScience.inputs.ModelDeploymentCategoryLogDetailsPredictArgs;
    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 testModelDeployment = new ModelDeployment("testModelDeployment", ModelDeploymentArgs.builder()
                .compartmentId(compartmentId)
                .modelDeploymentConfigurationDetails(ModelDeploymentModelDeploymentConfigurationDetailsArgs.builder()
                    .deploymentType(modelDeploymentModelDeploymentConfigurationDetailsDeploymentType)
                    .modelConfigurationDetails(ModelDeploymentModelDeploymentConfigurationDetailsModelConfigurationDetailsArgs.builder()
                        .instanceConfiguration(ModelDeploymentModelDeploymentConfigurationDetailsModelConfigurationDetailsInstanceConfigurationArgs.builder()
                            .instanceShapeName(testShape.name())
                            .modelDeploymentInstanceShapeConfigDetails(ModelDeploymentModelDeploymentConfigurationDetailsModelConfigurationDetailsInstanceConfigurationModelDeploymentInstanceShapeConfigDetailsArgs.builder()
                                .cpuBaseline(modelDeploymentModelDeploymentConfigurationDetailsModelConfigurationDetailsInstanceConfigurationModelDeploymentInstanceShapeConfigDetailsCpuBaseline)
                                .memoryInGbs(modelDeploymentModelDeploymentConfigurationDetailsModelConfigurationDetailsInstanceConfigurationModelDeploymentInstanceShapeConfigDetailsMemoryInGbs)
                                .ocpus(modelDeploymentModelDeploymentConfigurationDetailsModelConfigurationDetailsInstanceConfigurationModelDeploymentInstanceShapeConfigDetailsOcpus)
                                .build())
                            .subnetId(testSubnet.id())
                            .build())
                        .modelId(testModel.id())
                        .bandwidthMbps(modelDeploymentModelDeploymentConfigurationDetailsModelConfigurationDetailsBandwidthMbps)
                        .maximumBandwidthMbps(modelDeploymentModelDeploymentConfigurationDetailsModelConfigurationDetailsMaximumBandwidthMbps)
                        .scalingPolicy(ModelDeploymentModelDeploymentConfigurationDetailsModelConfigurationDetailsScalingPolicyArgs.builder()
                            .policyType(modelDeploymentModelDeploymentConfigurationDetailsModelConfigurationDetailsScalingPolicyPolicyType)
                            .autoScalingPolicies(ModelDeploymentModelDeploymentConfigurationDetailsModelConfigurationDetailsScalingPolicyAutoScalingPolicyArgs.builder()
                                .autoScalingPolicyType(modelDeploymentModelDeploymentConfigurationDetailsModelConfigurationDetailsScalingPolicyAutoScalingPoliciesAutoScalingPolicyType)
                                .initialInstanceCount(modelDeploymentModelDeploymentConfigurationDetailsModelConfigurationDetailsScalingPolicyAutoScalingPoliciesInitialInstanceCount)
                                .maximumInstanceCount(modelDeploymentModelDeploymentConfigurationDetailsModelConfigurationDetailsScalingPolicyAutoScalingPoliciesMaximumInstanceCount)
                                .minimumInstanceCount(modelDeploymentModelDeploymentConfigurationDetailsModelConfigurationDetailsScalingPolicyAutoScalingPoliciesMinimumInstanceCount)
                                .rules(ModelDeploymentModelDeploymentConfigurationDetailsModelConfigurationDetailsScalingPolicyAutoScalingPolicyRuleArgs.builder()
                                    .metricExpressionRuleType(modelDeploymentModelDeploymentConfigurationDetailsModelConfigurationDetailsScalingPolicyAutoScalingPoliciesRulesMetricExpressionRuleType)
                                    .scaleInConfiguration(ModelDeploymentModelDeploymentConfigurationDetailsModelConfigurationDetailsScalingPolicyAutoScalingPolicyRuleScaleInConfigurationArgs.builder()
                                        .instanceCountAdjustment(modelDeploymentModelDeploymentConfigurationDetailsModelConfigurationDetailsScalingPolicyAutoScalingPoliciesRulesScaleInConfigurationInstanceCountAdjustment)
                                        .pendingDuration(modelDeploymentModelDeploymentConfigurationDetailsModelConfigurationDetailsScalingPolicyAutoScalingPoliciesRulesScaleInConfigurationPendingDuration)
                                        .query(modelDeploymentModelDeploymentConfigurationDetailsModelConfigurationDetailsScalingPolicyAutoScalingPoliciesRulesScaleInConfigurationQuery)
                                        .scalingConfigurationType(modelDeploymentModelDeploymentConfigurationDetailsModelConfigurationDetailsScalingPolicyAutoScalingPoliciesRulesScaleInConfigurationScalingConfigurationType)
                                        .threshold(modelDeploymentModelDeploymentConfigurationDetailsModelConfigurationDetailsScalingPolicyAutoScalingPoliciesRulesScaleInConfigurationThreshold)
                                        .build())
                                    .scaleOutConfiguration(ModelDeploymentModelDeploymentConfigurationDetailsModelConfigurationDetailsScalingPolicyAutoScalingPolicyRuleScaleOutConfigurationArgs.builder()
                                        .instanceCountAdjustment(modelDeploymentModelDeploymentConfigurationDetailsModelConfigurationDetailsScalingPolicyAutoScalingPoliciesRulesScaleOutConfigurationInstanceCountAdjustment)
                                        .pendingDuration(modelDeploymentModelDeploymentConfigurationDetailsModelConfigurationDetailsScalingPolicyAutoScalingPoliciesRulesScaleOutConfigurationPendingDuration)
                                        .query(modelDeploymentModelDeploymentConfigurationDetailsModelConfigurationDetailsScalingPolicyAutoScalingPoliciesRulesScaleOutConfigurationQuery)
                                        .scalingConfigurationType(modelDeploymentModelDeploymentConfigurationDetailsModelConfigurationDetailsScalingPolicyAutoScalingPoliciesRulesScaleOutConfigurationScalingConfigurationType)
                                        .threshold(modelDeploymentModelDeploymentConfigurationDetailsModelConfigurationDetailsScalingPolicyAutoScalingPoliciesRulesScaleOutConfigurationThreshold)
                                        .build())
                                    .metricType(modelDeploymentModelDeploymentConfigurationDetailsModelConfigurationDetailsScalingPolicyAutoScalingPoliciesRulesMetricType)
                                    .build())
                                .build())
                            .coolDownInSeconds(modelDeploymentModelDeploymentConfigurationDetailsModelConfigurationDetailsScalingPolicyCoolDownInSeconds)
                            .instanceCount(modelDeploymentModelDeploymentConfigurationDetailsModelConfigurationDetailsScalingPolicyInstanceCount)
                            .isEnabled(modelDeploymentModelDeploymentConfigurationDetailsModelConfigurationDetailsScalingPolicyIsEnabled)
                            .build())
                        .build())
                    .environmentConfigurationDetails(ModelDeploymentModelDeploymentConfigurationDetailsEnvironmentConfigurationDetailsArgs.builder()
                        .environmentConfigurationType(modelDeploymentModelDeploymentConfigurationDetailsEnvironmentConfigurationDetailsEnvironmentConfigurationType)
                        .cmds(modelDeploymentModelDeploymentConfigurationDetailsEnvironmentConfigurationDetailsCmd)
                        .entrypoints(modelDeploymentModelDeploymentConfigurationDetailsEnvironmentConfigurationDetailsEntrypoint)
                        .environmentVariables(modelDeploymentModelDeploymentConfigurationDetailsEnvironmentConfigurationDetailsEnvironmentVariables)
                        .healthCheckPort(modelDeploymentModelDeploymentConfigurationDetailsEnvironmentConfigurationDetailsHealthCheckPort)
                        .image(modelDeploymentModelDeploymentConfigurationDetailsEnvironmentConfigurationDetailsImage)
                        .imageDigest(modelDeploymentModelDeploymentConfigurationDetailsEnvironmentConfigurationDetailsImageDigest)
                        .serverPort(modelDeploymentModelDeploymentConfigurationDetailsEnvironmentConfigurationDetailsServerPort)
                        .build())
                    .build())
                .projectId(testProject.id())
                .categoryLogDetails(ModelDeploymentCategoryLogDetailsArgs.builder()
                    .access(ModelDeploymentCategoryLogDetailsAccessArgs.builder()
                        .logGroupId(testLogGroup.id())
                        .logId(testLog.id())
                        .build())
                    .predict(ModelDeploymentCategoryLogDetailsPredictArgs.builder()
                        .logGroupId(testLogGroup.id())
                        .logId(testLog.id())
                        .build())
                    .build())
                .definedTags(Map.of("Operations.CostCenter", "42"))
                .description(modelDeploymentDescription)
                .displayName(modelDeploymentDisplayName)
                .freeformTags(Map.of("Department", "Finance"))
                .opcParentRptUrl(modelDeploymentOpcParentRptUrl)
                .build());
    
        }
    }
    
    resources:
      testModelDeployment:
        type: oci:DataScience:ModelDeployment
        name: test_model_deployment
        properties:
          compartmentId: ${compartmentId}
          modelDeploymentConfigurationDetails:
            deploymentType: ${modelDeploymentModelDeploymentConfigurationDetailsDeploymentType}
            modelConfigurationDetails:
              instanceConfiguration:
                instanceShapeName: ${testShape.name}
                modelDeploymentInstanceShapeConfigDetails:
                  cpuBaseline: ${modelDeploymentModelDeploymentConfigurationDetailsModelConfigurationDetailsInstanceConfigurationModelDeploymentInstanceShapeConfigDetailsCpuBaseline}
                  memoryInGbs: ${modelDeploymentModelDeploymentConfigurationDetailsModelConfigurationDetailsInstanceConfigurationModelDeploymentInstanceShapeConfigDetailsMemoryInGbs}
                  ocpus: ${modelDeploymentModelDeploymentConfigurationDetailsModelConfigurationDetailsInstanceConfigurationModelDeploymentInstanceShapeConfigDetailsOcpus}
                subnetId: ${testSubnet.id}
              modelId: ${testModel.id}
              bandwidthMbps: ${modelDeploymentModelDeploymentConfigurationDetailsModelConfigurationDetailsBandwidthMbps}
              maximumBandwidthMbps: ${modelDeploymentModelDeploymentConfigurationDetailsModelConfigurationDetailsMaximumBandwidthMbps}
              scalingPolicy:
                policyType: ${modelDeploymentModelDeploymentConfigurationDetailsModelConfigurationDetailsScalingPolicyPolicyType}
                autoScalingPolicies:
                  - autoScalingPolicyType: ${modelDeploymentModelDeploymentConfigurationDetailsModelConfigurationDetailsScalingPolicyAutoScalingPoliciesAutoScalingPolicyType}
                    initialInstanceCount: ${modelDeploymentModelDeploymentConfigurationDetailsModelConfigurationDetailsScalingPolicyAutoScalingPoliciesInitialInstanceCount}
                    maximumInstanceCount: ${modelDeploymentModelDeploymentConfigurationDetailsModelConfigurationDetailsScalingPolicyAutoScalingPoliciesMaximumInstanceCount}
                    minimumInstanceCount: ${modelDeploymentModelDeploymentConfigurationDetailsModelConfigurationDetailsScalingPolicyAutoScalingPoliciesMinimumInstanceCount}
                    rules:
                      - metricExpressionRuleType: ${modelDeploymentModelDeploymentConfigurationDetailsModelConfigurationDetailsScalingPolicyAutoScalingPoliciesRulesMetricExpressionRuleType}
                        scaleInConfiguration:
                          instanceCountAdjustment: ${modelDeploymentModelDeploymentConfigurationDetailsModelConfigurationDetailsScalingPolicyAutoScalingPoliciesRulesScaleInConfigurationInstanceCountAdjustment}
                          pendingDuration: ${modelDeploymentModelDeploymentConfigurationDetailsModelConfigurationDetailsScalingPolicyAutoScalingPoliciesRulesScaleInConfigurationPendingDuration}
                          query: ${modelDeploymentModelDeploymentConfigurationDetailsModelConfigurationDetailsScalingPolicyAutoScalingPoliciesRulesScaleInConfigurationQuery}
                          scalingConfigurationType: ${modelDeploymentModelDeploymentConfigurationDetailsModelConfigurationDetailsScalingPolicyAutoScalingPoliciesRulesScaleInConfigurationScalingConfigurationType}
                          threshold: ${modelDeploymentModelDeploymentConfigurationDetailsModelConfigurationDetailsScalingPolicyAutoScalingPoliciesRulesScaleInConfigurationThreshold}
                        scaleOutConfiguration:
                          instanceCountAdjustment: ${modelDeploymentModelDeploymentConfigurationDetailsModelConfigurationDetailsScalingPolicyAutoScalingPoliciesRulesScaleOutConfigurationInstanceCountAdjustment}
                          pendingDuration: ${modelDeploymentModelDeploymentConfigurationDetailsModelConfigurationDetailsScalingPolicyAutoScalingPoliciesRulesScaleOutConfigurationPendingDuration}
                          query: ${modelDeploymentModelDeploymentConfigurationDetailsModelConfigurationDetailsScalingPolicyAutoScalingPoliciesRulesScaleOutConfigurationQuery}
                          scalingConfigurationType: ${modelDeploymentModelDeploymentConfigurationDetailsModelConfigurationDetailsScalingPolicyAutoScalingPoliciesRulesScaleOutConfigurationScalingConfigurationType}
                          threshold: ${modelDeploymentModelDeploymentConfigurationDetailsModelConfigurationDetailsScalingPolicyAutoScalingPoliciesRulesScaleOutConfigurationThreshold}
                        metricType: ${modelDeploymentModelDeploymentConfigurationDetailsModelConfigurationDetailsScalingPolicyAutoScalingPoliciesRulesMetricType}
                coolDownInSeconds: ${modelDeploymentModelDeploymentConfigurationDetailsModelConfigurationDetailsScalingPolicyCoolDownInSeconds}
                instanceCount: ${modelDeploymentModelDeploymentConfigurationDetailsModelConfigurationDetailsScalingPolicyInstanceCount}
                isEnabled: ${modelDeploymentModelDeploymentConfigurationDetailsModelConfigurationDetailsScalingPolicyIsEnabled}
            environmentConfigurationDetails:
              environmentConfigurationType: ${modelDeploymentModelDeploymentConfigurationDetailsEnvironmentConfigurationDetailsEnvironmentConfigurationType}
              cmds: ${modelDeploymentModelDeploymentConfigurationDetailsEnvironmentConfigurationDetailsCmd}
              entrypoints: ${modelDeploymentModelDeploymentConfigurationDetailsEnvironmentConfigurationDetailsEntrypoint}
              environmentVariables: ${modelDeploymentModelDeploymentConfigurationDetailsEnvironmentConfigurationDetailsEnvironmentVariables}
              healthCheckPort: ${modelDeploymentModelDeploymentConfigurationDetailsEnvironmentConfigurationDetailsHealthCheckPort}
              image: ${modelDeploymentModelDeploymentConfigurationDetailsEnvironmentConfigurationDetailsImage}
              imageDigest: ${modelDeploymentModelDeploymentConfigurationDetailsEnvironmentConfigurationDetailsImageDigest}
              serverPort: ${modelDeploymentModelDeploymentConfigurationDetailsEnvironmentConfigurationDetailsServerPort}
          projectId: ${testProject.id}
          categoryLogDetails:
            access:
              logGroupId: ${testLogGroup.id}
              logId: ${testLog.id}
            predict:
              logGroupId: ${testLogGroup.id}
              logId: ${testLog.id}
          definedTags:
            Operations.CostCenter: '42'
          description: ${modelDeploymentDescription}
          displayName: ${modelDeploymentDisplayName}
          freeformTags:
            Department: Finance
          opcParentRptUrl: ${modelDeploymentOpcParentRptUrl}
    

    Create ModelDeployment Resource

    Resources are created with functions called constructors. To learn more about declaring and configuring resources, see Resources.

    Constructor syntax

    new ModelDeployment(name: string, args: ModelDeploymentArgs, opts?: CustomResourceOptions);
    @overload
    def ModelDeployment(resource_name: str,
                        args: ModelDeploymentArgs,
                        opts: Optional[ResourceOptions] = None)
    
    @overload
    def ModelDeployment(resource_name: str,
                        opts: Optional[ResourceOptions] = None,
                        compartment_id: Optional[str] = None,
                        model_deployment_configuration_details: Optional[_datascience.ModelDeploymentModelDeploymentConfigurationDetailsArgs] = None,
                        project_id: Optional[str] = None,
                        category_log_details: Optional[_datascience.ModelDeploymentCategoryLogDetailsArgs] = None,
                        defined_tags: Optional[Mapping[str, Any]] = None,
                        description: Optional[str] = None,
                        display_name: Optional[str] = None,
                        freeform_tags: Optional[Mapping[str, Any]] = None,
                        opc_parent_rpt_url: Optional[str] = None,
                        state: Optional[str] = None)
    func NewModelDeployment(ctx *Context, name string, args ModelDeploymentArgs, opts ...ResourceOption) (*ModelDeployment, error)
    public ModelDeployment(string name, ModelDeploymentArgs args, CustomResourceOptions? opts = null)
    public ModelDeployment(String name, ModelDeploymentArgs args)
    public ModelDeployment(String name, ModelDeploymentArgs args, CustomResourceOptions options)
    
    type: oci:DataScience:ModelDeployment
    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 ModelDeploymentArgs
    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 ModelDeploymentArgs
    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 ModelDeploymentArgs
    The arguments to resource properties.
    opts ResourceOption
    Bag of options to control resource's behavior.
    name string
    The unique name of the resource.
    args ModelDeploymentArgs
    The arguments to resource properties.
    opts CustomResourceOptions
    Bag of options to control resource's behavior.
    name String
    The unique name of the resource.
    args ModelDeploymentArgs
    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 modelDeploymentResource = new Oci.DataScience.ModelDeployment("modelDeploymentResource", new()
    {
        CompartmentId = "string",
        ModelDeploymentConfigurationDetails = new Oci.DataScience.Inputs.ModelDeploymentModelDeploymentConfigurationDetailsArgs
        {
            DeploymentType = "string",
            ModelConfigurationDetails = new Oci.DataScience.Inputs.ModelDeploymentModelDeploymentConfigurationDetailsModelConfigurationDetailsArgs
            {
                InstanceConfiguration = new Oci.DataScience.Inputs.ModelDeploymentModelDeploymentConfigurationDetailsModelConfigurationDetailsInstanceConfigurationArgs
                {
                    InstanceShapeName = "string",
                    ModelDeploymentInstanceShapeConfigDetails = new Oci.DataScience.Inputs.ModelDeploymentModelDeploymentConfigurationDetailsModelConfigurationDetailsInstanceConfigurationModelDeploymentInstanceShapeConfigDetailsArgs
                    {
                        CpuBaseline = "string",
                        MemoryInGbs = 0,
                        Ocpus = 0,
                    },
                    SubnetId = "string",
                },
                ModelId = "string",
                BandwidthMbps = 0,
                MaximumBandwidthMbps = 0,
                ScalingPolicy = new Oci.DataScience.Inputs.ModelDeploymentModelDeploymentConfigurationDetailsModelConfigurationDetailsScalingPolicyArgs
                {
                    PolicyType = "string",
                    AutoScalingPolicies = new[]
                    {
                        new Oci.DataScience.Inputs.ModelDeploymentModelDeploymentConfigurationDetailsModelConfigurationDetailsScalingPolicyAutoScalingPolicyArgs
                        {
                            AutoScalingPolicyType = "string",
                            InitialInstanceCount = 0,
                            MaximumInstanceCount = 0,
                            MinimumInstanceCount = 0,
                            Rules = new[]
                            {
                                new Oci.DataScience.Inputs.ModelDeploymentModelDeploymentConfigurationDetailsModelConfigurationDetailsScalingPolicyAutoScalingPolicyRuleArgs
                                {
                                    MetricExpressionRuleType = "string",
                                    ScaleInConfiguration = new Oci.DataScience.Inputs.ModelDeploymentModelDeploymentConfigurationDetailsModelConfigurationDetailsScalingPolicyAutoScalingPolicyRuleScaleInConfigurationArgs
                                    {
                                        InstanceCountAdjustment = 0,
                                        PendingDuration = "string",
                                        Query = "string",
                                        ScalingConfigurationType = "string",
                                        Threshold = 0,
                                    },
                                    ScaleOutConfiguration = new Oci.DataScience.Inputs.ModelDeploymentModelDeploymentConfigurationDetailsModelConfigurationDetailsScalingPolicyAutoScalingPolicyRuleScaleOutConfigurationArgs
                                    {
                                        InstanceCountAdjustment = 0,
                                        PendingDuration = "string",
                                        Query = "string",
                                        ScalingConfigurationType = "string",
                                        Threshold = 0,
                                    },
                                    MetricType = "string",
                                },
                            },
                        },
                    },
                    CoolDownInSeconds = 0,
                    InstanceCount = 0,
                    IsEnabled = false,
                },
            },
            EnvironmentConfigurationDetails = new Oci.DataScience.Inputs.ModelDeploymentModelDeploymentConfigurationDetailsEnvironmentConfigurationDetailsArgs
            {
                EnvironmentConfigurationType = "string",
                Cmds = new[]
                {
                    "string",
                },
                Entrypoints = new[]
                {
                    "string",
                },
                EnvironmentVariables = 
                {
                    { "string", "any" },
                },
                HealthCheckPort = 0,
                Image = "string",
                ImageDigest = "string",
                ServerPort = 0,
            },
        },
        ProjectId = "string",
        CategoryLogDetails = new Oci.DataScience.Inputs.ModelDeploymentCategoryLogDetailsArgs
        {
            Access = new Oci.DataScience.Inputs.ModelDeploymentCategoryLogDetailsAccessArgs
            {
                LogGroupId = "string",
                LogId = "string",
            },
            Predict = new Oci.DataScience.Inputs.ModelDeploymentCategoryLogDetailsPredictArgs
            {
                LogGroupId = "string",
                LogId = "string",
            },
        },
        DefinedTags = 
        {
            { "string", "any" },
        },
        Description = "string",
        DisplayName = "string",
        FreeformTags = 
        {
            { "string", "any" },
        },
        OpcParentRptUrl = "string",
        State = "string",
    });
    
    example, err := DataScience.NewModelDeployment(ctx, "modelDeploymentResource", &DataScience.ModelDeploymentArgs{
    	CompartmentId: pulumi.String("string"),
    	ModelDeploymentConfigurationDetails: &datascience.ModelDeploymentModelDeploymentConfigurationDetailsArgs{
    		DeploymentType: pulumi.String("string"),
    		ModelConfigurationDetails: &datascience.ModelDeploymentModelDeploymentConfigurationDetailsModelConfigurationDetailsArgs{
    			InstanceConfiguration: &datascience.ModelDeploymentModelDeploymentConfigurationDetailsModelConfigurationDetailsInstanceConfigurationArgs{
    				InstanceShapeName: pulumi.String("string"),
    				ModelDeploymentInstanceShapeConfigDetails: &datascience.ModelDeploymentModelDeploymentConfigurationDetailsModelConfigurationDetailsInstanceConfigurationModelDeploymentInstanceShapeConfigDetailsArgs{
    					CpuBaseline: pulumi.String("string"),
    					MemoryInGbs: pulumi.Float64(0),
    					Ocpus:       pulumi.Float64(0),
    				},
    				SubnetId: pulumi.String("string"),
    			},
    			ModelId:              pulumi.String("string"),
    			BandwidthMbps:        pulumi.Int(0),
    			MaximumBandwidthMbps: pulumi.Int(0),
    			ScalingPolicy: &datascience.ModelDeploymentModelDeploymentConfigurationDetailsModelConfigurationDetailsScalingPolicyArgs{
    				PolicyType: pulumi.String("string"),
    				AutoScalingPolicies: datascience.ModelDeploymentModelDeploymentConfigurationDetailsModelConfigurationDetailsScalingPolicyAutoScalingPolicyArray{
    					&datascience.ModelDeploymentModelDeploymentConfigurationDetailsModelConfigurationDetailsScalingPolicyAutoScalingPolicyArgs{
    						AutoScalingPolicyType: pulumi.String("string"),
    						InitialInstanceCount:  pulumi.Int(0),
    						MaximumInstanceCount:  pulumi.Int(0),
    						MinimumInstanceCount:  pulumi.Int(0),
    						Rules: datascience.ModelDeploymentModelDeploymentConfigurationDetailsModelConfigurationDetailsScalingPolicyAutoScalingPolicyRuleArray{
    							&datascience.ModelDeploymentModelDeploymentConfigurationDetailsModelConfigurationDetailsScalingPolicyAutoScalingPolicyRuleArgs{
    								MetricExpressionRuleType: pulumi.String("string"),
    								ScaleInConfiguration: &datascience.ModelDeploymentModelDeploymentConfigurationDetailsModelConfigurationDetailsScalingPolicyAutoScalingPolicyRuleScaleInConfigurationArgs{
    									InstanceCountAdjustment:  pulumi.Int(0),
    									PendingDuration:          pulumi.String("string"),
    									Query:                    pulumi.String("string"),
    									ScalingConfigurationType: pulumi.String("string"),
    									Threshold:                pulumi.Int(0),
    								},
    								ScaleOutConfiguration: &datascience.ModelDeploymentModelDeploymentConfigurationDetailsModelConfigurationDetailsScalingPolicyAutoScalingPolicyRuleScaleOutConfigurationArgs{
    									InstanceCountAdjustment:  pulumi.Int(0),
    									PendingDuration:          pulumi.String("string"),
    									Query:                    pulumi.String("string"),
    									ScalingConfigurationType: pulumi.String("string"),
    									Threshold:                pulumi.Int(0),
    								},
    								MetricType: pulumi.String("string"),
    							},
    						},
    					},
    				},
    				CoolDownInSeconds: pulumi.Int(0),
    				InstanceCount:     pulumi.Int(0),
    				IsEnabled:         pulumi.Bool(false),
    			},
    		},
    		EnvironmentConfigurationDetails: &datascience.ModelDeploymentModelDeploymentConfigurationDetailsEnvironmentConfigurationDetailsArgs{
    			EnvironmentConfigurationType: pulumi.String("string"),
    			Cmds: pulumi.StringArray{
    				pulumi.String("string"),
    			},
    			Entrypoints: pulumi.StringArray{
    				pulumi.String("string"),
    			},
    			EnvironmentVariables: pulumi.Map{
    				"string": pulumi.Any("any"),
    			},
    			HealthCheckPort: pulumi.Int(0),
    			Image:           pulumi.String("string"),
    			ImageDigest:     pulumi.String("string"),
    			ServerPort:      pulumi.Int(0),
    		},
    	},
    	ProjectId: pulumi.String("string"),
    	CategoryLogDetails: &datascience.ModelDeploymentCategoryLogDetailsArgs{
    		Access: &datascience.ModelDeploymentCategoryLogDetailsAccessArgs{
    			LogGroupId: pulumi.String("string"),
    			LogId:      pulumi.String("string"),
    		},
    		Predict: &datascience.ModelDeploymentCategoryLogDetailsPredictArgs{
    			LogGroupId: pulumi.String("string"),
    			LogId:      pulumi.String("string"),
    		},
    	},
    	DefinedTags: pulumi.Map{
    		"string": pulumi.Any("any"),
    	},
    	Description: pulumi.String("string"),
    	DisplayName: pulumi.String("string"),
    	FreeformTags: pulumi.Map{
    		"string": pulumi.Any("any"),
    	},
    	OpcParentRptUrl: pulumi.String("string"),
    	State:           pulumi.String("string"),
    })
    
    var modelDeploymentResource = new ModelDeployment("modelDeploymentResource", ModelDeploymentArgs.builder()
        .compartmentId("string")
        .modelDeploymentConfigurationDetails(ModelDeploymentModelDeploymentConfigurationDetailsArgs.builder()
            .deploymentType("string")
            .modelConfigurationDetails(ModelDeploymentModelDeploymentConfigurationDetailsModelConfigurationDetailsArgs.builder()
                .instanceConfiguration(ModelDeploymentModelDeploymentConfigurationDetailsModelConfigurationDetailsInstanceConfigurationArgs.builder()
                    .instanceShapeName("string")
                    .modelDeploymentInstanceShapeConfigDetails(ModelDeploymentModelDeploymentConfigurationDetailsModelConfigurationDetailsInstanceConfigurationModelDeploymentInstanceShapeConfigDetailsArgs.builder()
                        .cpuBaseline("string")
                        .memoryInGbs(0)
                        .ocpus(0)
                        .build())
                    .subnetId("string")
                    .build())
                .modelId("string")
                .bandwidthMbps(0)
                .maximumBandwidthMbps(0)
                .scalingPolicy(ModelDeploymentModelDeploymentConfigurationDetailsModelConfigurationDetailsScalingPolicyArgs.builder()
                    .policyType("string")
                    .autoScalingPolicies(ModelDeploymentModelDeploymentConfigurationDetailsModelConfigurationDetailsScalingPolicyAutoScalingPolicyArgs.builder()
                        .autoScalingPolicyType("string")
                        .initialInstanceCount(0)
                        .maximumInstanceCount(0)
                        .minimumInstanceCount(0)
                        .rules(ModelDeploymentModelDeploymentConfigurationDetailsModelConfigurationDetailsScalingPolicyAutoScalingPolicyRuleArgs.builder()
                            .metricExpressionRuleType("string")
                            .scaleInConfiguration(ModelDeploymentModelDeploymentConfigurationDetailsModelConfigurationDetailsScalingPolicyAutoScalingPolicyRuleScaleInConfigurationArgs.builder()
                                .instanceCountAdjustment(0)
                                .pendingDuration("string")
                                .query("string")
                                .scalingConfigurationType("string")
                                .threshold(0)
                                .build())
                            .scaleOutConfiguration(ModelDeploymentModelDeploymentConfigurationDetailsModelConfigurationDetailsScalingPolicyAutoScalingPolicyRuleScaleOutConfigurationArgs.builder()
                                .instanceCountAdjustment(0)
                                .pendingDuration("string")
                                .query("string")
                                .scalingConfigurationType("string")
                                .threshold(0)
                                .build())
                            .metricType("string")
                            .build())
                        .build())
                    .coolDownInSeconds(0)
                    .instanceCount(0)
                    .isEnabled(false)
                    .build())
                .build())
            .environmentConfigurationDetails(ModelDeploymentModelDeploymentConfigurationDetailsEnvironmentConfigurationDetailsArgs.builder()
                .environmentConfigurationType("string")
                .cmds("string")
                .entrypoints("string")
                .environmentVariables(Map.of("string", "any"))
                .healthCheckPort(0)
                .image("string")
                .imageDigest("string")
                .serverPort(0)
                .build())
            .build())
        .projectId("string")
        .categoryLogDetails(ModelDeploymentCategoryLogDetailsArgs.builder()
            .access(ModelDeploymentCategoryLogDetailsAccessArgs.builder()
                .logGroupId("string")
                .logId("string")
                .build())
            .predict(ModelDeploymentCategoryLogDetailsPredictArgs.builder()
                .logGroupId("string")
                .logId("string")
                .build())
            .build())
        .definedTags(Map.of("string", "any"))
        .description("string")
        .displayName("string")
        .freeformTags(Map.of("string", "any"))
        .opcParentRptUrl("string")
        .state("string")
        .build());
    
    model_deployment_resource = oci.data_science.ModelDeployment("modelDeploymentResource",
        compartment_id="string",
        model_deployment_configuration_details=oci.data_science.ModelDeploymentModelDeploymentConfigurationDetailsArgs(
            deployment_type="string",
            model_configuration_details=oci.data_science.ModelDeploymentModelDeploymentConfigurationDetailsModelConfigurationDetailsArgs(
                instance_configuration=oci.data_science.ModelDeploymentModelDeploymentConfigurationDetailsModelConfigurationDetailsInstanceConfigurationArgs(
                    instance_shape_name="string",
                    model_deployment_instance_shape_config_details=oci.data_science.ModelDeploymentModelDeploymentConfigurationDetailsModelConfigurationDetailsInstanceConfigurationModelDeploymentInstanceShapeConfigDetailsArgs(
                        cpu_baseline="string",
                        memory_in_gbs=0,
                        ocpus=0,
                    ),
                    subnet_id="string",
                ),
                model_id="string",
                bandwidth_mbps=0,
                maximum_bandwidth_mbps=0,
                scaling_policy=oci.data_science.ModelDeploymentModelDeploymentConfigurationDetailsModelConfigurationDetailsScalingPolicyArgs(
                    policy_type="string",
                    auto_scaling_policies=[oci.data_science.ModelDeploymentModelDeploymentConfigurationDetailsModelConfigurationDetailsScalingPolicyAutoScalingPolicyArgs(
                        auto_scaling_policy_type="string",
                        initial_instance_count=0,
                        maximum_instance_count=0,
                        minimum_instance_count=0,
                        rules=[oci.data_science.ModelDeploymentModelDeploymentConfigurationDetailsModelConfigurationDetailsScalingPolicyAutoScalingPolicyRuleArgs(
                            metric_expression_rule_type="string",
                            scale_in_configuration=oci.data_science.ModelDeploymentModelDeploymentConfigurationDetailsModelConfigurationDetailsScalingPolicyAutoScalingPolicyRuleScaleInConfigurationArgs(
                                instance_count_adjustment=0,
                                pending_duration="string",
                                query="string",
                                scaling_configuration_type="string",
                                threshold=0,
                            ),
                            scale_out_configuration=oci.data_science.ModelDeploymentModelDeploymentConfigurationDetailsModelConfigurationDetailsScalingPolicyAutoScalingPolicyRuleScaleOutConfigurationArgs(
                                instance_count_adjustment=0,
                                pending_duration="string",
                                query="string",
                                scaling_configuration_type="string",
                                threshold=0,
                            ),
                            metric_type="string",
                        )],
                    )],
                    cool_down_in_seconds=0,
                    instance_count=0,
                    is_enabled=False,
                ),
            ),
            environment_configuration_details=oci.data_science.ModelDeploymentModelDeploymentConfigurationDetailsEnvironmentConfigurationDetailsArgs(
                environment_configuration_type="string",
                cmds=["string"],
                entrypoints=["string"],
                environment_variables={
                    "string": "any",
                },
                health_check_port=0,
                image="string",
                image_digest="string",
                server_port=0,
            ),
        ),
        project_id="string",
        category_log_details=oci.data_science.ModelDeploymentCategoryLogDetailsArgs(
            access=oci.data_science.ModelDeploymentCategoryLogDetailsAccessArgs(
                log_group_id="string",
                log_id="string",
            ),
            predict=oci.data_science.ModelDeploymentCategoryLogDetailsPredictArgs(
                log_group_id="string",
                log_id="string",
            ),
        ),
        defined_tags={
            "string": "any",
        },
        description="string",
        display_name="string",
        freeform_tags={
            "string": "any",
        },
        opc_parent_rpt_url="string",
        state="string")
    
    const modelDeploymentResource = new oci.datascience.ModelDeployment("modelDeploymentResource", {
        compartmentId: "string",
        modelDeploymentConfigurationDetails: {
            deploymentType: "string",
            modelConfigurationDetails: {
                instanceConfiguration: {
                    instanceShapeName: "string",
                    modelDeploymentInstanceShapeConfigDetails: {
                        cpuBaseline: "string",
                        memoryInGbs: 0,
                        ocpus: 0,
                    },
                    subnetId: "string",
                },
                modelId: "string",
                bandwidthMbps: 0,
                maximumBandwidthMbps: 0,
                scalingPolicy: {
                    policyType: "string",
                    autoScalingPolicies: [{
                        autoScalingPolicyType: "string",
                        initialInstanceCount: 0,
                        maximumInstanceCount: 0,
                        minimumInstanceCount: 0,
                        rules: [{
                            metricExpressionRuleType: "string",
                            scaleInConfiguration: {
                                instanceCountAdjustment: 0,
                                pendingDuration: "string",
                                query: "string",
                                scalingConfigurationType: "string",
                                threshold: 0,
                            },
                            scaleOutConfiguration: {
                                instanceCountAdjustment: 0,
                                pendingDuration: "string",
                                query: "string",
                                scalingConfigurationType: "string",
                                threshold: 0,
                            },
                            metricType: "string",
                        }],
                    }],
                    coolDownInSeconds: 0,
                    instanceCount: 0,
                    isEnabled: false,
                },
            },
            environmentConfigurationDetails: {
                environmentConfigurationType: "string",
                cmds: ["string"],
                entrypoints: ["string"],
                environmentVariables: {
                    string: "any",
                },
                healthCheckPort: 0,
                image: "string",
                imageDigest: "string",
                serverPort: 0,
            },
        },
        projectId: "string",
        categoryLogDetails: {
            access: {
                logGroupId: "string",
                logId: "string",
            },
            predict: {
                logGroupId: "string",
                logId: "string",
            },
        },
        definedTags: {
            string: "any",
        },
        description: "string",
        displayName: "string",
        freeformTags: {
            string: "any",
        },
        opcParentRptUrl: "string",
        state: "string",
    });
    
    type: oci:DataScience:ModelDeployment
    properties:
        categoryLogDetails:
            access:
                logGroupId: string
                logId: string
            predict:
                logGroupId: string
                logId: string
        compartmentId: string
        definedTags:
            string: any
        description: string
        displayName: string
        freeformTags:
            string: any
        modelDeploymentConfigurationDetails:
            deploymentType: string
            environmentConfigurationDetails:
                cmds:
                    - string
                entrypoints:
                    - string
                environmentConfigurationType: string
                environmentVariables:
                    string: any
                healthCheckPort: 0
                image: string
                imageDigest: string
                serverPort: 0
            modelConfigurationDetails:
                bandwidthMbps: 0
                instanceConfiguration:
                    instanceShapeName: string
                    modelDeploymentInstanceShapeConfigDetails:
                        cpuBaseline: string
                        memoryInGbs: 0
                        ocpus: 0
                    subnetId: string
                maximumBandwidthMbps: 0
                modelId: string
                scalingPolicy:
                    autoScalingPolicies:
                        - autoScalingPolicyType: string
                          initialInstanceCount: 0
                          maximumInstanceCount: 0
                          minimumInstanceCount: 0
                          rules:
                            - metricExpressionRuleType: string
                              metricType: string
                              scaleInConfiguration:
                                instanceCountAdjustment: 0
                                pendingDuration: string
                                query: string
                                scalingConfigurationType: string
                                threshold: 0
                              scaleOutConfiguration:
                                instanceCountAdjustment: 0
                                pendingDuration: string
                                query: string
                                scalingConfigurationType: string
                                threshold: 0
                    coolDownInSeconds: 0
                    instanceCount: 0
                    isEnabled: false
                    policyType: string
        opcParentRptUrl: string
        projectId: string
        state: string
    

    ModelDeployment Resource Properties

    To learn more about resource properties and how to use them, see Inputs and Outputs in the Architecture and Concepts docs.

    Inputs

    The ModelDeployment resource accepts the following input properties:

    CompartmentId string
    (Updatable) The OCID of the compartment where you want to create the model deployment.
    ModelDeploymentConfigurationDetails ModelDeploymentModelDeploymentConfigurationDetails
    (Updatable) The model deployment configuration details.
    ProjectId string
    The OCID of the project to associate with the model deployment.
    CategoryLogDetails ModelDeploymentCategoryLogDetails
    (Updatable) The log details for each category.
    DefinedTags Dictionary<string, object>
    (Updatable) Defined tags for this resource. Each key is predefined and scoped to a namespace. See Resource Tags. Example: {"Operations.CostCenter": "42"}
    Description string
    (Updatable) A short description of the model deployment.
    DisplayName string
    (Updatable) A user-friendly display name for the resource. Does not have to be unique, and can be modified. Avoid entering confidential information. Example: My ModelDeployment
    FreeformTags Dictionary<string, object>
    (Updatable) Free-form tags for this resource. Each tag is a simple key-value pair with no predefined name, type, or namespace. See Resource Tags. Example: {"Department": "Finance"}
    OpcParentRptUrl string
    URL to fetch the Resource Principal Token from the parent resource.
    State string

    (Updatable) The target state for the Model Deployment. Could be set to ACTIVE or INACTIVE.

    ** IMPORTANT ** Any change to a property that does not support update will force the destruction and recreation of the resource with the new property values

    CompartmentId string
    (Updatable) The OCID of the compartment where you want to create the model deployment.
    ModelDeploymentConfigurationDetails ModelDeploymentModelDeploymentConfigurationDetailsArgs
    (Updatable) The model deployment configuration details.
    ProjectId string
    The OCID of the project to associate with the model deployment.
    CategoryLogDetails ModelDeploymentCategoryLogDetailsArgs
    (Updatable) The log details for each category.
    DefinedTags map[string]interface{}
    (Updatable) Defined tags for this resource. Each key is predefined and scoped to a namespace. See Resource Tags. Example: {"Operations.CostCenter": "42"}
    Description string
    (Updatable) A short description of the model deployment.
    DisplayName string
    (Updatable) A user-friendly display name for the resource. Does not have to be unique, and can be modified. Avoid entering confidential information. Example: My ModelDeployment
    FreeformTags map[string]interface{}
    (Updatable) Free-form tags for this resource. Each tag is a simple key-value pair with no predefined name, type, or namespace. See Resource Tags. Example: {"Department": "Finance"}
    OpcParentRptUrl string
    URL to fetch the Resource Principal Token from the parent resource.
    State string

    (Updatable) The target state for the Model Deployment. Could be set to ACTIVE or INACTIVE.

    ** IMPORTANT ** Any change to a property that does not support update will force the destruction and recreation of the resource with the new property values

    compartmentId String
    (Updatable) The OCID of the compartment where you want to create the model deployment.
    modelDeploymentConfigurationDetails ModelDeploymentModelDeploymentConfigurationDetails
    (Updatable) The model deployment configuration details.
    projectId String
    The OCID of the project to associate with the model deployment.
    categoryLogDetails ModelDeploymentCategoryLogDetails
    (Updatable) The log details for each category.
    definedTags Map<String,Object>
    (Updatable) Defined tags for this resource. Each key is predefined and scoped to a namespace. See Resource Tags. Example: {"Operations.CostCenter": "42"}
    description String
    (Updatable) A short description of the model deployment.
    displayName String
    (Updatable) A user-friendly display name for the resource. Does not have to be unique, and can be modified. Avoid entering confidential information. Example: My ModelDeployment
    freeformTags Map<String,Object>
    (Updatable) Free-form tags for this resource. Each tag is a simple key-value pair with no predefined name, type, or namespace. See Resource Tags. Example: {"Department": "Finance"}
    opcParentRptUrl String
    URL to fetch the Resource Principal Token from the parent resource.
    state String

    (Updatable) The target state for the Model Deployment. Could be set to ACTIVE or INACTIVE.

    ** IMPORTANT ** Any change to a property that does not support update will force the destruction and recreation of the resource with the new property values

    compartmentId string
    (Updatable) The OCID of the compartment where you want to create the model deployment.
    modelDeploymentConfigurationDetails ModelDeploymentModelDeploymentConfigurationDetails
    (Updatable) The model deployment configuration details.
    projectId string
    The OCID of the project to associate with the model deployment.
    categoryLogDetails ModelDeploymentCategoryLogDetails
    (Updatable) The log details for each category.
    definedTags {[key: string]: any}
    (Updatable) Defined tags for this resource. Each key is predefined and scoped to a namespace. See Resource Tags. Example: {"Operations.CostCenter": "42"}
    description string
    (Updatable) A short description of the model deployment.
    displayName string
    (Updatable) A user-friendly display name for the resource. Does not have to be unique, and can be modified. Avoid entering confidential information. Example: My ModelDeployment
    freeformTags {[key: string]: any}
    (Updatable) Free-form tags for this resource. Each tag is a simple key-value pair with no predefined name, type, or namespace. See Resource Tags. Example: {"Department": "Finance"}
    opcParentRptUrl string
    URL to fetch the Resource Principal Token from the parent resource.
    state string

    (Updatable) The target state for the Model Deployment. Could be set to ACTIVE or INACTIVE.

    ** IMPORTANT ** Any change to a property that does not support update will force the destruction and recreation of the resource with the new property values

    compartment_id str
    (Updatable) The OCID of the compartment where you want to create the model deployment.
    model_deployment_configuration_details datascience.ModelDeploymentModelDeploymentConfigurationDetailsArgs
    (Updatable) The model deployment configuration details.
    project_id str
    The OCID of the project to associate with the model deployment.
    category_log_details datascience.ModelDeploymentCategoryLogDetailsArgs
    (Updatable) The log details for each category.
    defined_tags Mapping[str, Any]
    (Updatable) Defined tags for this resource. Each key is predefined and scoped to a namespace. See Resource Tags. Example: {"Operations.CostCenter": "42"}
    description str
    (Updatable) A short description of the model deployment.
    display_name str
    (Updatable) A user-friendly display name for the resource. Does not have to be unique, and can be modified. Avoid entering confidential information. Example: My ModelDeployment
    freeform_tags Mapping[str, Any]
    (Updatable) Free-form tags for this resource. Each tag is a simple key-value pair with no predefined name, type, or namespace. See Resource Tags. Example: {"Department": "Finance"}
    opc_parent_rpt_url str
    URL to fetch the Resource Principal Token from the parent resource.
    state str

    (Updatable) The target state for the Model Deployment. Could be set to ACTIVE or INACTIVE.

    ** IMPORTANT ** Any change to a property that does not support update will force the destruction and recreation of the resource with the new property values

    compartmentId String
    (Updatable) The OCID of the compartment where you want to create the model deployment.
    modelDeploymentConfigurationDetails Property Map
    (Updatable) The model deployment configuration details.
    projectId String
    The OCID of the project to associate with the model deployment.
    categoryLogDetails Property Map
    (Updatable) The log details for each category.
    definedTags Map<Any>
    (Updatable) Defined tags for this resource. Each key is predefined and scoped to a namespace. See Resource Tags. Example: {"Operations.CostCenter": "42"}
    description String
    (Updatable) A short description of the model deployment.
    displayName String
    (Updatable) A user-friendly display name for the resource. Does not have to be unique, and can be modified. Avoid entering confidential information. Example: My ModelDeployment
    freeformTags Map<Any>
    (Updatable) Free-form tags for this resource. Each tag is a simple key-value pair with no predefined name, type, or namespace. See Resource Tags. Example: {"Department": "Finance"}
    opcParentRptUrl String
    URL to fetch the Resource Principal Token from the parent resource.
    state String

    (Updatable) The target state for the Model Deployment. Could be set to ACTIVE or INACTIVE.

    ** IMPORTANT ** Any change to a property that does not support update will force the destruction and recreation of the resource with the new property values

    Outputs

    All input properties are implicitly available as output properties. Additionally, the ModelDeployment resource produces the following output properties:

    CreatedBy string
    The OCID of the user who created the model deployment.
    Id string
    The provider-assigned unique ID for this managed resource.
    LifecycleDetails string
    Details about the state of the model deployment.
    ModelDeploymentSystemDatas List<ModelDeploymentModelDeploymentSystemData>
    Model deployment system data.
    ModelDeploymentUrl string
    The URL to interact with the model deployment.
    TimeCreated string
    The date and time the resource was created, in the timestamp format defined by RFC3339. Example: 2019-08-25T21:10:29.41Z
    CreatedBy string
    The OCID of the user who created the model deployment.
    Id string
    The provider-assigned unique ID for this managed resource.
    LifecycleDetails string
    Details about the state of the model deployment.
    ModelDeploymentSystemDatas []ModelDeploymentModelDeploymentSystemData
    Model deployment system data.
    ModelDeploymentUrl string
    The URL to interact with the model deployment.
    TimeCreated string
    The date and time the resource was created, in the timestamp format defined by RFC3339. Example: 2019-08-25T21:10:29.41Z
    createdBy String
    The OCID of the user who created the model deployment.
    id String
    The provider-assigned unique ID for this managed resource.
    lifecycleDetails String
    Details about the state of the model deployment.
    modelDeploymentSystemDatas List<ModelDeploymentModelDeploymentSystemData>
    Model deployment system data.
    modelDeploymentUrl String
    The URL to interact with the model deployment.
    timeCreated String
    The date and time the resource was created, in the timestamp format defined by RFC3339. Example: 2019-08-25T21:10:29.41Z
    createdBy string
    The OCID of the user who created the model deployment.
    id string
    The provider-assigned unique ID for this managed resource.
    lifecycleDetails string
    Details about the state of the model deployment.
    modelDeploymentSystemDatas ModelDeploymentModelDeploymentSystemData[]
    Model deployment system data.
    modelDeploymentUrl string
    The URL to interact with the model deployment.
    timeCreated string
    The date and time the resource was created, in the timestamp format defined by RFC3339. Example: 2019-08-25T21:10:29.41Z
    created_by str
    The OCID of the user who created the model deployment.
    id str
    The provider-assigned unique ID for this managed resource.
    lifecycle_details str
    Details about the state of the model deployment.
    model_deployment_system_datas Sequence[datascience.ModelDeploymentModelDeploymentSystemData]
    Model deployment system data.
    model_deployment_url str
    The URL to interact with the model deployment.
    time_created str
    The date and time the resource was created, in the timestamp format defined by RFC3339. Example: 2019-08-25T21:10:29.41Z
    createdBy String
    The OCID of the user who created the model deployment.
    id String
    The provider-assigned unique ID for this managed resource.
    lifecycleDetails String
    Details about the state of the model deployment.
    modelDeploymentSystemDatas List<Property Map>
    Model deployment system data.
    modelDeploymentUrl String
    The URL to interact with the model deployment.
    timeCreated String
    The date and time the resource was created, in the timestamp format defined by RFC3339. Example: 2019-08-25T21:10:29.41Z

    Look up Existing ModelDeployment Resource

    Get an existing ModelDeployment 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?: ModelDeploymentState, opts?: CustomResourceOptions): ModelDeployment
    @staticmethod
    def get(resource_name: str,
            id: str,
            opts: Optional[ResourceOptions] = None,
            category_log_details: Optional[_datascience.ModelDeploymentCategoryLogDetailsArgs] = None,
            compartment_id: Optional[str] = None,
            created_by: Optional[str] = None,
            defined_tags: Optional[Mapping[str, Any]] = None,
            description: Optional[str] = None,
            display_name: Optional[str] = None,
            freeform_tags: Optional[Mapping[str, Any]] = None,
            lifecycle_details: Optional[str] = None,
            model_deployment_configuration_details: Optional[_datascience.ModelDeploymentModelDeploymentConfigurationDetailsArgs] = None,
            model_deployment_system_datas: Optional[Sequence[_datascience.ModelDeploymentModelDeploymentSystemDataArgs]] = None,
            model_deployment_url: Optional[str] = None,
            opc_parent_rpt_url: Optional[str] = None,
            project_id: Optional[str] = None,
            state: Optional[str] = None,
            time_created: Optional[str] = None) -> ModelDeployment
    func GetModelDeployment(ctx *Context, name string, id IDInput, state *ModelDeploymentState, opts ...ResourceOption) (*ModelDeployment, error)
    public static ModelDeployment Get(string name, Input<string> id, ModelDeploymentState? state, CustomResourceOptions? opts = null)
    public static ModelDeployment get(String name, Output<String> id, ModelDeploymentState 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.
    The following state arguments are supported:
    CategoryLogDetails ModelDeploymentCategoryLogDetails
    (Updatable) The log details for each category.
    CompartmentId string
    (Updatable) The OCID of the compartment where you want to create the model deployment.
    CreatedBy string
    The OCID of the user who created the model deployment.
    DefinedTags Dictionary<string, object>
    (Updatable) Defined tags for this resource. Each key is predefined and scoped to a namespace. See Resource Tags. Example: {"Operations.CostCenter": "42"}
    Description string
    (Updatable) A short description of the model deployment.
    DisplayName string
    (Updatable) A user-friendly display name for the resource. Does not have to be unique, and can be modified. Avoid entering confidential information. Example: My ModelDeployment
    FreeformTags Dictionary<string, object>
    (Updatable) Free-form tags for this resource. Each tag is a simple key-value pair with no predefined name, type, or namespace. See Resource Tags. Example: {"Department": "Finance"}
    LifecycleDetails string
    Details about the state of the model deployment.
    ModelDeploymentConfigurationDetails ModelDeploymentModelDeploymentConfigurationDetails
    (Updatable) The model deployment configuration details.
    ModelDeploymentSystemDatas List<ModelDeploymentModelDeploymentSystemData>
    Model deployment system data.
    ModelDeploymentUrl string
    The URL to interact with the model deployment.
    OpcParentRptUrl string
    URL to fetch the Resource Principal Token from the parent resource.
    ProjectId string
    The OCID of the project to associate with the model deployment.
    State string

    (Updatable) The target state for the Model Deployment. Could be set to ACTIVE or INACTIVE.

    ** IMPORTANT ** Any change to a property that does not support update will force the destruction and recreation of the resource with the new property values

    TimeCreated string
    The date and time the resource was created, in the timestamp format defined by RFC3339. Example: 2019-08-25T21:10:29.41Z
    CategoryLogDetails ModelDeploymentCategoryLogDetailsArgs
    (Updatable) The log details for each category.
    CompartmentId string
    (Updatable) The OCID of the compartment where you want to create the model deployment.
    CreatedBy string
    The OCID of the user who created the model deployment.
    DefinedTags map[string]interface{}
    (Updatable) Defined tags for this resource. Each key is predefined and scoped to a namespace. See Resource Tags. Example: {"Operations.CostCenter": "42"}
    Description string
    (Updatable) A short description of the model deployment.
    DisplayName string
    (Updatable) A user-friendly display name for the resource. Does not have to be unique, and can be modified. Avoid entering confidential information. Example: My ModelDeployment
    FreeformTags map[string]interface{}
    (Updatable) Free-form tags for this resource. Each tag is a simple key-value pair with no predefined name, type, or namespace. See Resource Tags. Example: {"Department": "Finance"}
    LifecycleDetails string
    Details about the state of the model deployment.
    ModelDeploymentConfigurationDetails ModelDeploymentModelDeploymentConfigurationDetailsArgs
    (Updatable) The model deployment configuration details.
    ModelDeploymentSystemDatas []ModelDeploymentModelDeploymentSystemDataArgs
    Model deployment system data.
    ModelDeploymentUrl string
    The URL to interact with the model deployment.
    OpcParentRptUrl string
    URL to fetch the Resource Principal Token from the parent resource.
    ProjectId string
    The OCID of the project to associate with the model deployment.
    State string

    (Updatable) The target state for the Model Deployment. Could be set to ACTIVE or INACTIVE.

    ** IMPORTANT ** Any change to a property that does not support update will force the destruction and recreation of the resource with the new property values

    TimeCreated string
    The date and time the resource was created, in the timestamp format defined by RFC3339. Example: 2019-08-25T21:10:29.41Z
    categoryLogDetails ModelDeploymentCategoryLogDetails
    (Updatable) The log details for each category.
    compartmentId String
    (Updatable) The OCID of the compartment where you want to create the model deployment.
    createdBy String
    The OCID of the user who created the model deployment.
    definedTags Map<String,Object>
    (Updatable) Defined tags for this resource. Each key is predefined and scoped to a namespace. See Resource Tags. Example: {"Operations.CostCenter": "42"}
    description String
    (Updatable) A short description of the model deployment.
    displayName String
    (Updatable) A user-friendly display name for the resource. Does not have to be unique, and can be modified. Avoid entering confidential information. Example: My ModelDeployment
    freeformTags Map<String,Object>
    (Updatable) Free-form tags for this resource. Each tag is a simple key-value pair with no predefined name, type, or namespace. See Resource Tags. Example: {"Department": "Finance"}
    lifecycleDetails String
    Details about the state of the model deployment.
    modelDeploymentConfigurationDetails ModelDeploymentModelDeploymentConfigurationDetails
    (Updatable) The model deployment configuration details.
    modelDeploymentSystemDatas List<ModelDeploymentModelDeploymentSystemData>
    Model deployment system data.
    modelDeploymentUrl String
    The URL to interact with the model deployment.
    opcParentRptUrl String
    URL to fetch the Resource Principal Token from the parent resource.
    projectId String
    The OCID of the project to associate with the model deployment.
    state String

    (Updatable) The target state for the Model Deployment. Could be set to ACTIVE or INACTIVE.

    ** IMPORTANT ** Any change to a property that does not support update will force the destruction and recreation of the resource with the new property values

    timeCreated String
    The date and time the resource was created, in the timestamp format defined by RFC3339. Example: 2019-08-25T21:10:29.41Z
    categoryLogDetails ModelDeploymentCategoryLogDetails
    (Updatable) The log details for each category.
    compartmentId string
    (Updatable) The OCID of the compartment where you want to create the model deployment.
    createdBy string
    The OCID of the user who created the model deployment.
    definedTags {[key: string]: any}
    (Updatable) Defined tags for this resource. Each key is predefined and scoped to a namespace. See Resource Tags. Example: {"Operations.CostCenter": "42"}
    description string
    (Updatable) A short description of the model deployment.
    displayName string
    (Updatable) A user-friendly display name for the resource. Does not have to be unique, and can be modified. Avoid entering confidential information. Example: My ModelDeployment
    freeformTags {[key: string]: any}
    (Updatable) Free-form tags for this resource. Each tag is a simple key-value pair with no predefined name, type, or namespace. See Resource Tags. Example: {"Department": "Finance"}
    lifecycleDetails string
    Details about the state of the model deployment.
    modelDeploymentConfigurationDetails ModelDeploymentModelDeploymentConfigurationDetails
    (Updatable) The model deployment configuration details.
    modelDeploymentSystemDatas ModelDeploymentModelDeploymentSystemData[]
    Model deployment system data.
    modelDeploymentUrl string
    The URL to interact with the model deployment.
    opcParentRptUrl string
    URL to fetch the Resource Principal Token from the parent resource.
    projectId string
    The OCID of the project to associate with the model deployment.
    state string

    (Updatable) The target state for the Model Deployment. Could be set to ACTIVE or INACTIVE.

    ** IMPORTANT ** Any change to a property that does not support update will force the destruction and recreation of the resource with the new property values

    timeCreated string
    The date and time the resource was created, in the timestamp format defined by RFC3339. Example: 2019-08-25T21:10:29.41Z
    category_log_details datascience.ModelDeploymentCategoryLogDetailsArgs
    (Updatable) The log details for each category.
    compartment_id str
    (Updatable) The OCID of the compartment where you want to create the model deployment.
    created_by str
    The OCID of the user who created the model deployment.
    defined_tags Mapping[str, Any]
    (Updatable) Defined tags for this resource. Each key is predefined and scoped to a namespace. See Resource Tags. Example: {"Operations.CostCenter": "42"}
    description str
    (Updatable) A short description of the model deployment.
    display_name str
    (Updatable) A user-friendly display name for the resource. Does not have to be unique, and can be modified. Avoid entering confidential information. Example: My ModelDeployment
    freeform_tags Mapping[str, Any]
    (Updatable) Free-form tags for this resource. Each tag is a simple key-value pair with no predefined name, type, or namespace. See Resource Tags. Example: {"Department": "Finance"}
    lifecycle_details str
    Details about the state of the model deployment.
    model_deployment_configuration_details datascience.ModelDeploymentModelDeploymentConfigurationDetailsArgs
    (Updatable) The model deployment configuration details.
    model_deployment_system_datas Sequence[datascience.ModelDeploymentModelDeploymentSystemDataArgs]
    Model deployment system data.
    model_deployment_url str
    The URL to interact with the model deployment.
    opc_parent_rpt_url str
    URL to fetch the Resource Principal Token from the parent resource.
    project_id str
    The OCID of the project to associate with the model deployment.
    state str

    (Updatable) The target state for the Model Deployment. Could be set to ACTIVE or INACTIVE.

    ** IMPORTANT ** Any change to a property that does not support update will force the destruction and recreation of the resource with the new property values

    time_created str
    The date and time the resource was created, in the timestamp format defined by RFC3339. Example: 2019-08-25T21:10:29.41Z
    categoryLogDetails Property Map
    (Updatable) The log details for each category.
    compartmentId String
    (Updatable) The OCID of the compartment where you want to create the model deployment.
    createdBy String
    The OCID of the user who created the model deployment.
    definedTags Map<Any>
    (Updatable) Defined tags for this resource. Each key is predefined and scoped to a namespace. See Resource Tags. Example: {"Operations.CostCenter": "42"}
    description String
    (Updatable) A short description of the model deployment.
    displayName String
    (Updatable) A user-friendly display name for the resource. Does not have to be unique, and can be modified. Avoid entering confidential information. Example: My ModelDeployment
    freeformTags Map<Any>
    (Updatable) Free-form tags for this resource. Each tag is a simple key-value pair with no predefined name, type, or namespace. See Resource Tags. Example: {"Department": "Finance"}
    lifecycleDetails String
    Details about the state of the model deployment.
    modelDeploymentConfigurationDetails Property Map
    (Updatable) The model deployment configuration details.
    modelDeploymentSystemDatas List<Property Map>
    Model deployment system data.
    modelDeploymentUrl String
    The URL to interact with the model deployment.
    opcParentRptUrl String
    URL to fetch the Resource Principal Token from the parent resource.
    projectId String
    The OCID of the project to associate with the model deployment.
    state String

    (Updatable) The target state for the Model Deployment. Could be set to ACTIVE or INACTIVE.

    ** IMPORTANT ** Any change to a property that does not support update will force the destruction and recreation of the resource with the new property values

    timeCreated String
    The date and time the resource was created, in the timestamp format defined by RFC3339. Example: 2019-08-25T21:10:29.41Z

    Supporting Types

    ModelDeploymentCategoryLogDetails, ModelDeploymentCategoryLogDetailsArgs

    access Property Map
    (Updatable) The log details.
    predict Property Map
    (Updatable) The log details.

    ModelDeploymentCategoryLogDetailsAccess, ModelDeploymentCategoryLogDetailsAccessArgs

    LogGroupId string
    (Updatable) The OCID of a log group to work with.
    LogId string
    (Updatable) The OCID of a log to work with.
    LogGroupId string
    (Updatable) The OCID of a log group to work with.
    LogId string
    (Updatable) The OCID of a log to work with.
    logGroupId String
    (Updatable) The OCID of a log group to work with.
    logId String
    (Updatable) The OCID of a log to work with.
    logGroupId string
    (Updatable) The OCID of a log group to work with.
    logId string
    (Updatable) The OCID of a log to work with.
    log_group_id str
    (Updatable) The OCID of a log group to work with.
    log_id str
    (Updatable) The OCID of a log to work with.
    logGroupId String
    (Updatable) The OCID of a log group to work with.
    logId String
    (Updatable) The OCID of a log to work with.

    ModelDeploymentCategoryLogDetailsPredict, ModelDeploymentCategoryLogDetailsPredictArgs

    LogGroupId string
    (Updatable) The OCID of a log group to work with.
    LogId string
    (Updatable) The OCID of a log to work with.
    LogGroupId string
    (Updatable) The OCID of a log group to work with.
    LogId string
    (Updatable) The OCID of a log to work with.
    logGroupId String
    (Updatable) The OCID of a log group to work with.
    logId String
    (Updatable) The OCID of a log to work with.
    logGroupId string
    (Updatable) The OCID of a log group to work with.
    logId string
    (Updatable) The OCID of a log to work with.
    log_group_id str
    (Updatable) The OCID of a log group to work with.
    log_id str
    (Updatable) The OCID of a log to work with.
    logGroupId String
    (Updatable) The OCID of a log group to work with.
    logId String
    (Updatable) The OCID of a log to work with.

    ModelDeploymentModelDeploymentConfigurationDetails, ModelDeploymentModelDeploymentConfigurationDetailsArgs

    DeploymentType string
    (Updatable) The type of the model deployment.
    ModelConfigurationDetails ModelDeploymentModelDeploymentConfigurationDetailsModelConfigurationDetails
    (Updatable) The model configuration details.
    EnvironmentConfigurationDetails ModelDeploymentModelDeploymentConfigurationDetailsEnvironmentConfigurationDetails
    (Updatable) The configuration to carry the environment details thats used in Model Deployment creation
    DeploymentType string
    (Updatable) The type of the model deployment.
    ModelConfigurationDetails ModelDeploymentModelDeploymentConfigurationDetailsModelConfigurationDetails
    (Updatable) The model configuration details.
    EnvironmentConfigurationDetails ModelDeploymentModelDeploymentConfigurationDetailsEnvironmentConfigurationDetails
    (Updatable) The configuration to carry the environment details thats used in Model Deployment creation
    deploymentType String
    (Updatable) The type of the model deployment.
    modelConfigurationDetails ModelDeploymentModelDeploymentConfigurationDetailsModelConfigurationDetails
    (Updatable) The model configuration details.
    environmentConfigurationDetails ModelDeploymentModelDeploymentConfigurationDetailsEnvironmentConfigurationDetails
    (Updatable) The configuration to carry the environment details thats used in Model Deployment creation
    deploymentType string
    (Updatable) The type of the model deployment.
    modelConfigurationDetails ModelDeploymentModelDeploymentConfigurationDetailsModelConfigurationDetails
    (Updatable) The model configuration details.
    environmentConfigurationDetails ModelDeploymentModelDeploymentConfigurationDetailsEnvironmentConfigurationDetails
    (Updatable) The configuration to carry the environment details thats used in Model Deployment creation
    deployment_type str
    (Updatable) The type of the model deployment.
    model_configuration_details datascience.ModelDeploymentModelDeploymentConfigurationDetailsModelConfigurationDetails
    (Updatable) The model configuration details.
    environment_configuration_details datascience.ModelDeploymentModelDeploymentConfigurationDetailsEnvironmentConfigurationDetails
    (Updatable) The configuration to carry the environment details thats used in Model Deployment creation
    deploymentType String
    (Updatable) The type of the model deployment.
    modelConfigurationDetails Property Map
    (Updatable) The model configuration details.
    environmentConfigurationDetails Property Map
    (Updatable) The configuration to carry the environment details thats used in Model Deployment creation

    ModelDeploymentModelDeploymentConfigurationDetailsEnvironmentConfigurationDetails, ModelDeploymentModelDeploymentConfigurationDetailsEnvironmentConfigurationDetailsArgs

    EnvironmentConfigurationType string
    (Updatable) The environment configuration type
    Cmds List<string>
    (Updatable) The container image run CMD as a list of strings. Use CMD as arguments to the ENTRYPOINT or the only command to run in the absence of an ENTRYPOINT. The combined size of CMD and ENTRYPOINT must be less than 2048 bytes.
    Entrypoints List<string>
    (Updatable) The container image run ENTRYPOINT as a list of strings. Accept the CMD as extra arguments. The combined size of CMD and ENTRYPOINT must be less than 2048 bytes. More information on how CMD and ENTRYPOINT interact are here.
    EnvironmentVariables Dictionary<string, object>
    (Updatable) Environment variables to set for the web server container. The size of envVars must be less than 2048 bytes. Key should be under 32 characters. Key should contain only letters, digits and underscore (_) Key should start with a letter. Key should have at least 2 characters. Key should not end with underscore eg. TEST_ Key if added cannot be empty. Value can be empty. No specific size limits on individual Values. But overall environment variables is limited to 2048 bytes. Key can't be reserved Model Deployment environment variables.
    HealthCheckPort int
    (Updatable) The port on which the container HEALTHCHECK would listen. The port can be anything between 1024 and 65535. The following ports cannot be used 24224, 8446, 8447.
    Image string
    (Updatable) The full path to the Oracle Container Repository (OCIR) registry, image, and tag in a canonical format. Acceptable format: <region>.ocir.io/<registry>/<image>:<tag> <region>.ocir.io/<registry>/<image>:<tag>@digest
    ImageDigest string
    (Updatable) The digest of the container image. For example, sha256:881303a6b2738834d795a32b4a98eb0e5e3d1cad590a712d1e04f9b2fa90a030
    ServerPort int
    (Updatable) The port on which the web server serving the inference is running. The port can be anything between 1024 and 65535. The following ports cannot be used 24224, 8446, 8447.
    EnvironmentConfigurationType string
    (Updatable) The environment configuration type
    Cmds []string
    (Updatable) The container image run CMD as a list of strings. Use CMD as arguments to the ENTRYPOINT or the only command to run in the absence of an ENTRYPOINT. The combined size of CMD and ENTRYPOINT must be less than 2048 bytes.
    Entrypoints []string
    (Updatable) The container image run ENTRYPOINT as a list of strings. Accept the CMD as extra arguments. The combined size of CMD and ENTRYPOINT must be less than 2048 bytes. More information on how CMD and ENTRYPOINT interact are here.
    EnvironmentVariables map[string]interface{}
    (Updatable) Environment variables to set for the web server container. The size of envVars must be less than 2048 bytes. Key should be under 32 characters. Key should contain only letters, digits and underscore (_) Key should start with a letter. Key should have at least 2 characters. Key should not end with underscore eg. TEST_ Key if added cannot be empty. Value can be empty. No specific size limits on individual Values. But overall environment variables is limited to 2048 bytes. Key can't be reserved Model Deployment environment variables.
    HealthCheckPort int
    (Updatable) The port on which the container HEALTHCHECK would listen. The port can be anything between 1024 and 65535. The following ports cannot be used 24224, 8446, 8447.
    Image string
    (Updatable) The full path to the Oracle Container Repository (OCIR) registry, image, and tag in a canonical format. Acceptable format: <region>.ocir.io/<registry>/<image>:<tag> <region>.ocir.io/<registry>/<image>:<tag>@digest
    ImageDigest string
    (Updatable) The digest of the container image. For example, sha256:881303a6b2738834d795a32b4a98eb0e5e3d1cad590a712d1e04f9b2fa90a030
    ServerPort int
    (Updatable) The port on which the web server serving the inference is running. The port can be anything between 1024 and 65535. The following ports cannot be used 24224, 8446, 8447.
    environmentConfigurationType String
    (Updatable) The environment configuration type
    cmds List<String>
    (Updatable) The container image run CMD as a list of strings. Use CMD as arguments to the ENTRYPOINT or the only command to run in the absence of an ENTRYPOINT. The combined size of CMD and ENTRYPOINT must be less than 2048 bytes.
    entrypoints List<String>
    (Updatable) The container image run ENTRYPOINT as a list of strings. Accept the CMD as extra arguments. The combined size of CMD and ENTRYPOINT must be less than 2048 bytes. More information on how CMD and ENTRYPOINT interact are here.
    environmentVariables Map<String,Object>
    (Updatable) Environment variables to set for the web server container. The size of envVars must be less than 2048 bytes. Key should be under 32 characters. Key should contain only letters, digits and underscore (_) Key should start with a letter. Key should have at least 2 characters. Key should not end with underscore eg. TEST_ Key if added cannot be empty. Value can be empty. No specific size limits on individual Values. But overall environment variables is limited to 2048 bytes. Key can't be reserved Model Deployment environment variables.
    healthCheckPort Integer
    (Updatable) The port on which the container HEALTHCHECK would listen. The port can be anything between 1024 and 65535. The following ports cannot be used 24224, 8446, 8447.
    image String
    (Updatable) The full path to the Oracle Container Repository (OCIR) registry, image, and tag in a canonical format. Acceptable format: <region>.ocir.io/<registry>/<image>:<tag> <region>.ocir.io/<registry>/<image>:<tag>@digest
    imageDigest String
    (Updatable) The digest of the container image. For example, sha256:881303a6b2738834d795a32b4a98eb0e5e3d1cad590a712d1e04f9b2fa90a030
    serverPort Integer
    (Updatable) The port on which the web server serving the inference is running. The port can be anything between 1024 and 65535. The following ports cannot be used 24224, 8446, 8447.
    environmentConfigurationType string
    (Updatable) The environment configuration type
    cmds string[]
    (Updatable) The container image run CMD as a list of strings. Use CMD as arguments to the ENTRYPOINT or the only command to run in the absence of an ENTRYPOINT. The combined size of CMD and ENTRYPOINT must be less than 2048 bytes.
    entrypoints string[]
    (Updatable) The container image run ENTRYPOINT as a list of strings. Accept the CMD as extra arguments. The combined size of CMD and ENTRYPOINT must be less than 2048 bytes. More information on how CMD and ENTRYPOINT interact are here.
    environmentVariables {[key: string]: any}
    (Updatable) Environment variables to set for the web server container. The size of envVars must be less than 2048 bytes. Key should be under 32 characters. Key should contain only letters, digits and underscore (_) Key should start with a letter. Key should have at least 2 characters. Key should not end with underscore eg. TEST_ Key if added cannot be empty. Value can be empty. No specific size limits on individual Values. But overall environment variables is limited to 2048 bytes. Key can't be reserved Model Deployment environment variables.
    healthCheckPort number
    (Updatable) The port on which the container HEALTHCHECK would listen. The port can be anything between 1024 and 65535. The following ports cannot be used 24224, 8446, 8447.
    image string
    (Updatable) The full path to the Oracle Container Repository (OCIR) registry, image, and tag in a canonical format. Acceptable format: <region>.ocir.io/<registry>/<image>:<tag> <region>.ocir.io/<registry>/<image>:<tag>@digest
    imageDigest string
    (Updatable) The digest of the container image. For example, sha256:881303a6b2738834d795a32b4a98eb0e5e3d1cad590a712d1e04f9b2fa90a030
    serverPort number
    (Updatable) The port on which the web server serving the inference is running. The port can be anything between 1024 and 65535. The following ports cannot be used 24224, 8446, 8447.
    environment_configuration_type str
    (Updatable) The environment configuration type
    cmds Sequence[str]
    (Updatable) The container image run CMD as a list of strings. Use CMD as arguments to the ENTRYPOINT or the only command to run in the absence of an ENTRYPOINT. The combined size of CMD and ENTRYPOINT must be less than 2048 bytes.
    entrypoints Sequence[str]
    (Updatable) The container image run ENTRYPOINT as a list of strings. Accept the CMD as extra arguments. The combined size of CMD and ENTRYPOINT must be less than 2048 bytes. More information on how CMD and ENTRYPOINT interact are here.
    environment_variables Mapping[str, Any]
    (Updatable) Environment variables to set for the web server container. The size of envVars must be less than 2048 bytes. Key should be under 32 characters. Key should contain only letters, digits and underscore (_) Key should start with a letter. Key should have at least 2 characters. Key should not end with underscore eg. TEST_ Key if added cannot be empty. Value can be empty. No specific size limits on individual Values. But overall environment variables is limited to 2048 bytes. Key can't be reserved Model Deployment environment variables.
    health_check_port int
    (Updatable) The port on which the container HEALTHCHECK would listen. The port can be anything between 1024 and 65535. The following ports cannot be used 24224, 8446, 8447.
    image str
    (Updatable) The full path to the Oracle Container Repository (OCIR) registry, image, and tag in a canonical format. Acceptable format: <region>.ocir.io/<registry>/<image>:<tag> <region>.ocir.io/<registry>/<image>:<tag>@digest
    image_digest str
    (Updatable) The digest of the container image. For example, sha256:881303a6b2738834d795a32b4a98eb0e5e3d1cad590a712d1e04f9b2fa90a030
    server_port int
    (Updatable) The port on which the web server serving the inference is running. The port can be anything between 1024 and 65535. The following ports cannot be used 24224, 8446, 8447.
    environmentConfigurationType String
    (Updatable) The environment configuration type
    cmds List<String>
    (Updatable) The container image run CMD as a list of strings. Use CMD as arguments to the ENTRYPOINT or the only command to run in the absence of an ENTRYPOINT. The combined size of CMD and ENTRYPOINT must be less than 2048 bytes.
    entrypoints List<String>
    (Updatable) The container image run ENTRYPOINT as a list of strings. Accept the CMD as extra arguments. The combined size of CMD and ENTRYPOINT must be less than 2048 bytes. More information on how CMD and ENTRYPOINT interact are here.
    environmentVariables Map<Any>
    (Updatable) Environment variables to set for the web server container. The size of envVars must be less than 2048 bytes. Key should be under 32 characters. Key should contain only letters, digits and underscore (_) Key should start with a letter. Key should have at least 2 characters. Key should not end with underscore eg. TEST_ Key if added cannot be empty. Value can be empty. No specific size limits on individual Values. But overall environment variables is limited to 2048 bytes. Key can't be reserved Model Deployment environment variables.
    healthCheckPort Number
    (Updatable) The port on which the container HEALTHCHECK would listen. The port can be anything between 1024 and 65535. The following ports cannot be used 24224, 8446, 8447.
    image String
    (Updatable) The full path to the Oracle Container Repository (OCIR) registry, image, and tag in a canonical format. Acceptable format: <region>.ocir.io/<registry>/<image>:<tag> <region>.ocir.io/<registry>/<image>:<tag>@digest
    imageDigest String
    (Updatable) The digest of the container image. For example, sha256:881303a6b2738834d795a32b4a98eb0e5e3d1cad590a712d1e04f9b2fa90a030
    serverPort Number
    (Updatable) The port on which the web server serving the inference is running. The port can be anything between 1024 and 65535. The following ports cannot be used 24224, 8446, 8447.

    ModelDeploymentModelDeploymentConfigurationDetailsModelConfigurationDetails, ModelDeploymentModelDeploymentConfigurationDetailsModelConfigurationDetailsArgs

    InstanceConfiguration ModelDeploymentModelDeploymentConfigurationDetailsModelConfigurationDetailsInstanceConfiguration
    (Updatable) The model deployment instance configuration
    ModelId string
    (Updatable) The OCID of the model you want to deploy.
    BandwidthMbps int
    (Updatable) The minimum network bandwidth for the model deployment.
    MaximumBandwidthMbps int
    (Updatable) The maximum network bandwidth for the model deployment.
    ScalingPolicy ModelDeploymentModelDeploymentConfigurationDetailsModelConfigurationDetailsScalingPolicy
    (Updatable) The scaling policy to apply to each model of the deployment.
    InstanceConfiguration ModelDeploymentModelDeploymentConfigurationDetailsModelConfigurationDetailsInstanceConfiguration
    (Updatable) The model deployment instance configuration
    ModelId string
    (Updatable) The OCID of the model you want to deploy.
    BandwidthMbps int
    (Updatable) The minimum network bandwidth for the model deployment.
    MaximumBandwidthMbps int
    (Updatable) The maximum network bandwidth for the model deployment.
    ScalingPolicy ModelDeploymentModelDeploymentConfigurationDetailsModelConfigurationDetailsScalingPolicy
    (Updatable) The scaling policy to apply to each model of the deployment.
    instanceConfiguration ModelDeploymentModelDeploymentConfigurationDetailsModelConfigurationDetailsInstanceConfiguration
    (Updatable) The model deployment instance configuration
    modelId String
    (Updatable) The OCID of the model you want to deploy.
    bandwidthMbps Integer
    (Updatable) The minimum network bandwidth for the model deployment.
    maximumBandwidthMbps Integer
    (Updatable) The maximum network bandwidth for the model deployment.
    scalingPolicy ModelDeploymentModelDeploymentConfigurationDetailsModelConfigurationDetailsScalingPolicy
    (Updatable) The scaling policy to apply to each model of the deployment.
    instanceConfiguration ModelDeploymentModelDeploymentConfigurationDetailsModelConfigurationDetailsInstanceConfiguration
    (Updatable) The model deployment instance configuration
    modelId string
    (Updatable) The OCID of the model you want to deploy.
    bandwidthMbps number
    (Updatable) The minimum network bandwidth for the model deployment.
    maximumBandwidthMbps number
    (Updatable) The maximum network bandwidth for the model deployment.
    scalingPolicy ModelDeploymentModelDeploymentConfigurationDetailsModelConfigurationDetailsScalingPolicy
    (Updatable) The scaling policy to apply to each model of the deployment.
    instance_configuration datascience.ModelDeploymentModelDeploymentConfigurationDetailsModelConfigurationDetailsInstanceConfiguration
    (Updatable) The model deployment instance configuration
    model_id str
    (Updatable) The OCID of the model you want to deploy.
    bandwidth_mbps int
    (Updatable) The minimum network bandwidth for the model deployment.
    maximum_bandwidth_mbps int
    (Updatable) The maximum network bandwidth for the model deployment.
    scaling_policy datascience.ModelDeploymentModelDeploymentConfigurationDetailsModelConfigurationDetailsScalingPolicy
    (Updatable) The scaling policy to apply to each model of the deployment.
    instanceConfiguration Property Map
    (Updatable) The model deployment instance configuration
    modelId String
    (Updatable) The OCID of the model you want to deploy.
    bandwidthMbps Number
    (Updatable) The minimum network bandwidth for the model deployment.
    maximumBandwidthMbps Number
    (Updatable) The maximum network bandwidth for the model deployment.
    scalingPolicy Property Map
    (Updatable) The scaling policy to apply to each model of the deployment.

    ModelDeploymentModelDeploymentConfigurationDetailsModelConfigurationDetailsInstanceConfiguration, ModelDeploymentModelDeploymentConfigurationDetailsModelConfigurationDetailsInstanceConfigurationArgs

    InstanceShapeName string
    (Updatable) The shape used to launch the model deployment instances.
    ModelDeploymentInstanceShapeConfigDetails ModelDeploymentModelDeploymentConfigurationDetailsModelConfigurationDetailsInstanceConfigurationModelDeploymentInstanceShapeConfigDetails
    (Updatable) Details for the model-deployment instance shape configuration.
    SubnetId string
    (Updatable) A model deployment instance is provided with a VNIC for network access. This specifies the OCID of the subnet to create a VNIC in. The subnet should be in a VCN with a NAT/SGW gateway for egress.
    InstanceShapeName string
    (Updatable) The shape used to launch the model deployment instances.
    ModelDeploymentInstanceShapeConfigDetails ModelDeploymentModelDeploymentConfigurationDetailsModelConfigurationDetailsInstanceConfigurationModelDeploymentInstanceShapeConfigDetails
    (Updatable) Details for the model-deployment instance shape configuration.
    SubnetId string
    (Updatable) A model deployment instance is provided with a VNIC for network access. This specifies the OCID of the subnet to create a VNIC in. The subnet should be in a VCN with a NAT/SGW gateway for egress.
    instanceShapeName String
    (Updatable) The shape used to launch the model deployment instances.
    modelDeploymentInstanceShapeConfigDetails ModelDeploymentModelDeploymentConfigurationDetailsModelConfigurationDetailsInstanceConfigurationModelDeploymentInstanceShapeConfigDetails
    (Updatable) Details for the model-deployment instance shape configuration.
    subnetId String
    (Updatable) A model deployment instance is provided with a VNIC for network access. This specifies the OCID of the subnet to create a VNIC in. The subnet should be in a VCN with a NAT/SGW gateway for egress.
    instanceShapeName string
    (Updatable) The shape used to launch the model deployment instances.
    modelDeploymentInstanceShapeConfigDetails ModelDeploymentModelDeploymentConfigurationDetailsModelConfigurationDetailsInstanceConfigurationModelDeploymentInstanceShapeConfigDetails
    (Updatable) Details for the model-deployment instance shape configuration.
    subnetId string
    (Updatable) A model deployment instance is provided with a VNIC for network access. This specifies the OCID of the subnet to create a VNIC in. The subnet should be in a VCN with a NAT/SGW gateway for egress.
    instance_shape_name str
    (Updatable) The shape used to launch the model deployment instances.
    model_deployment_instance_shape_config_details datascience.ModelDeploymentModelDeploymentConfigurationDetailsModelConfigurationDetailsInstanceConfigurationModelDeploymentInstanceShapeConfigDetails
    (Updatable) Details for the model-deployment instance shape configuration.
    subnet_id str
    (Updatable) A model deployment instance is provided with a VNIC for network access. This specifies the OCID of the subnet to create a VNIC in. The subnet should be in a VCN with a NAT/SGW gateway for egress.
    instanceShapeName String
    (Updatable) The shape used to launch the model deployment instances.
    modelDeploymentInstanceShapeConfigDetails Property Map
    (Updatable) Details for the model-deployment instance shape configuration.
    subnetId String
    (Updatable) A model deployment instance is provided with a VNIC for network access. This specifies the OCID of the subnet to create a VNIC in. The subnet should be in a VCN with a NAT/SGW gateway for egress.

    ModelDeploymentModelDeploymentConfigurationDetailsModelConfigurationDetailsInstanceConfigurationModelDeploymentInstanceShapeConfigDetails, ModelDeploymentModelDeploymentConfigurationDetailsModelConfigurationDetailsInstanceConfigurationModelDeploymentInstanceShapeConfigDetailsArgs

    CpuBaseline string
    (Updatable) The baseline OCPU utilization for a subcore burstable VM instance. If this attribute is left blank, it will default to BASELINE_1_1. The following values are supported: BASELINE_1_8 - baseline usage is 1/8 of an OCPU. BASELINE_1_2 - baseline usage is 1/2 of an OCPU. BASELINE_1_1 - baseline usage is an entire OCPU. This represents a non-burstable instance.
    MemoryInGbs double
    (Updatable) A model-deployment instance of type VM.Standard.E3.Flex or VM.Standard.E4.Flex allows the memory to be specified with in the range of 6 to 1024 GB. VM.Standard3.Flex memory range is between 6 to 512 GB and VM.Optimized3.Flex memory range is between 6 to 256 GB.
    Ocpus double
    (Updatable) A model-deployment instance of type VM.Standard.E3.Flex or VM.Standard.E4.Flex allows the ocpu count to be specified with in the range of 1 to 64 ocpu. VM.Standard3.Flex OCPU range is between 1 to 32 ocpu and for VM.Optimized3.Flex OCPU range is 1 to 18 ocpu.
    CpuBaseline string
    (Updatable) The baseline OCPU utilization for a subcore burstable VM instance. If this attribute is left blank, it will default to BASELINE_1_1. The following values are supported: BASELINE_1_8 - baseline usage is 1/8 of an OCPU. BASELINE_1_2 - baseline usage is 1/2 of an OCPU. BASELINE_1_1 - baseline usage is an entire OCPU. This represents a non-burstable instance.
    MemoryInGbs float64
    (Updatable) A model-deployment instance of type VM.Standard.E3.Flex or VM.Standard.E4.Flex allows the memory to be specified with in the range of 6 to 1024 GB. VM.Standard3.Flex memory range is between 6 to 512 GB and VM.Optimized3.Flex memory range is between 6 to 256 GB.
    Ocpus float64
    (Updatable) A model-deployment instance of type VM.Standard.E3.Flex or VM.Standard.E4.Flex allows the ocpu count to be specified with in the range of 1 to 64 ocpu. VM.Standard3.Flex OCPU range is between 1 to 32 ocpu and for VM.Optimized3.Flex OCPU range is 1 to 18 ocpu.
    cpuBaseline String
    (Updatable) The baseline OCPU utilization for a subcore burstable VM instance. If this attribute is left blank, it will default to BASELINE_1_1. The following values are supported: BASELINE_1_8 - baseline usage is 1/8 of an OCPU. BASELINE_1_2 - baseline usage is 1/2 of an OCPU. BASELINE_1_1 - baseline usage is an entire OCPU. This represents a non-burstable instance.
    memoryInGbs Double
    (Updatable) A model-deployment instance of type VM.Standard.E3.Flex or VM.Standard.E4.Flex allows the memory to be specified with in the range of 6 to 1024 GB. VM.Standard3.Flex memory range is between 6 to 512 GB and VM.Optimized3.Flex memory range is between 6 to 256 GB.
    ocpus Double
    (Updatable) A model-deployment instance of type VM.Standard.E3.Flex or VM.Standard.E4.Flex allows the ocpu count to be specified with in the range of 1 to 64 ocpu. VM.Standard3.Flex OCPU range is between 1 to 32 ocpu and for VM.Optimized3.Flex OCPU range is 1 to 18 ocpu.
    cpuBaseline string
    (Updatable) The baseline OCPU utilization for a subcore burstable VM instance. If this attribute is left blank, it will default to BASELINE_1_1. The following values are supported: BASELINE_1_8 - baseline usage is 1/8 of an OCPU. BASELINE_1_2 - baseline usage is 1/2 of an OCPU. BASELINE_1_1 - baseline usage is an entire OCPU. This represents a non-burstable instance.
    memoryInGbs number
    (Updatable) A model-deployment instance of type VM.Standard.E3.Flex or VM.Standard.E4.Flex allows the memory to be specified with in the range of 6 to 1024 GB. VM.Standard3.Flex memory range is between 6 to 512 GB and VM.Optimized3.Flex memory range is between 6 to 256 GB.
    ocpus number
    (Updatable) A model-deployment instance of type VM.Standard.E3.Flex or VM.Standard.E4.Flex allows the ocpu count to be specified with in the range of 1 to 64 ocpu. VM.Standard3.Flex OCPU range is between 1 to 32 ocpu and for VM.Optimized3.Flex OCPU range is 1 to 18 ocpu.
    cpu_baseline str
    (Updatable) The baseline OCPU utilization for a subcore burstable VM instance. If this attribute is left blank, it will default to BASELINE_1_1. The following values are supported: BASELINE_1_8 - baseline usage is 1/8 of an OCPU. BASELINE_1_2 - baseline usage is 1/2 of an OCPU. BASELINE_1_1 - baseline usage is an entire OCPU. This represents a non-burstable instance.
    memory_in_gbs float
    (Updatable) A model-deployment instance of type VM.Standard.E3.Flex or VM.Standard.E4.Flex allows the memory to be specified with in the range of 6 to 1024 GB. VM.Standard3.Flex memory range is between 6 to 512 GB and VM.Optimized3.Flex memory range is between 6 to 256 GB.
    ocpus float
    (Updatable) A model-deployment instance of type VM.Standard.E3.Flex or VM.Standard.E4.Flex allows the ocpu count to be specified with in the range of 1 to 64 ocpu. VM.Standard3.Flex OCPU range is between 1 to 32 ocpu and for VM.Optimized3.Flex OCPU range is 1 to 18 ocpu.
    cpuBaseline String
    (Updatable) The baseline OCPU utilization for a subcore burstable VM instance. If this attribute is left blank, it will default to BASELINE_1_1. The following values are supported: BASELINE_1_8 - baseline usage is 1/8 of an OCPU. BASELINE_1_2 - baseline usage is 1/2 of an OCPU. BASELINE_1_1 - baseline usage is an entire OCPU. This represents a non-burstable instance.
    memoryInGbs Number
    (Updatable) A model-deployment instance of type VM.Standard.E3.Flex or VM.Standard.E4.Flex allows the memory to be specified with in the range of 6 to 1024 GB. VM.Standard3.Flex memory range is between 6 to 512 GB and VM.Optimized3.Flex memory range is between 6 to 256 GB.
    ocpus Number
    (Updatable) A model-deployment instance of type VM.Standard.E3.Flex or VM.Standard.E4.Flex allows the ocpu count to be specified with in the range of 1 to 64 ocpu. VM.Standard3.Flex OCPU range is between 1 to 32 ocpu and for VM.Optimized3.Flex OCPU range is 1 to 18 ocpu.

    ModelDeploymentModelDeploymentConfigurationDetailsModelConfigurationDetailsScalingPolicy, ModelDeploymentModelDeploymentConfigurationDetailsModelConfigurationDetailsScalingPolicyArgs

    PolicyType string
    (Updatable) The type of scaling policy.
    AutoScalingPolicies List<ModelDeploymentModelDeploymentConfigurationDetailsModelConfigurationDetailsScalingPolicyAutoScalingPolicy>
    (Updatable) The list of autoscaling policy details.
    CoolDownInSeconds int
    (Updatable) For threshold-based autoscaling policies, this value is the minimum period of time to wait between scaling actions. The cooldown period gives the system time to stabilize before rescaling. The minimum value is 600 seconds, which is also the default. The cooldown period starts when the model deployment becomes ACTIVE after the scaling operation.
    InstanceCount int
    (Updatable) The number of instances for the model deployment.
    IsEnabled bool
    (Updatable) Whether the autoscaling policy is enabled.
    PolicyType string
    (Updatable) The type of scaling policy.
    AutoScalingPolicies []ModelDeploymentModelDeploymentConfigurationDetailsModelConfigurationDetailsScalingPolicyAutoScalingPolicy
    (Updatable) The list of autoscaling policy details.
    CoolDownInSeconds int
    (Updatable) For threshold-based autoscaling policies, this value is the minimum period of time to wait between scaling actions. The cooldown period gives the system time to stabilize before rescaling. The minimum value is 600 seconds, which is also the default. The cooldown period starts when the model deployment becomes ACTIVE after the scaling operation.
    InstanceCount int
    (Updatable) The number of instances for the model deployment.
    IsEnabled bool
    (Updatable) Whether the autoscaling policy is enabled.
    policyType String
    (Updatable) The type of scaling policy.
    autoScalingPolicies List<ModelDeploymentModelDeploymentConfigurationDetailsModelConfigurationDetailsScalingPolicyAutoScalingPolicy>
    (Updatable) The list of autoscaling policy details.
    coolDownInSeconds Integer
    (Updatable) For threshold-based autoscaling policies, this value is the minimum period of time to wait between scaling actions. The cooldown period gives the system time to stabilize before rescaling. The minimum value is 600 seconds, which is also the default. The cooldown period starts when the model deployment becomes ACTIVE after the scaling operation.
    instanceCount Integer
    (Updatable) The number of instances for the model deployment.
    isEnabled Boolean
    (Updatable) Whether the autoscaling policy is enabled.
    policyType string
    (Updatable) The type of scaling policy.
    autoScalingPolicies ModelDeploymentModelDeploymentConfigurationDetailsModelConfigurationDetailsScalingPolicyAutoScalingPolicy[]
    (Updatable) The list of autoscaling policy details.
    coolDownInSeconds number
    (Updatable) For threshold-based autoscaling policies, this value is the minimum period of time to wait between scaling actions. The cooldown period gives the system time to stabilize before rescaling. The minimum value is 600 seconds, which is also the default. The cooldown period starts when the model deployment becomes ACTIVE after the scaling operation.
    instanceCount number
    (Updatable) The number of instances for the model deployment.
    isEnabled boolean
    (Updatable) Whether the autoscaling policy is enabled.
    policy_type str
    (Updatable) The type of scaling policy.
    auto_scaling_policies Sequence[datascience.ModelDeploymentModelDeploymentConfigurationDetailsModelConfigurationDetailsScalingPolicyAutoScalingPolicy]
    (Updatable) The list of autoscaling policy details.
    cool_down_in_seconds int
    (Updatable) For threshold-based autoscaling policies, this value is the minimum period of time to wait between scaling actions. The cooldown period gives the system time to stabilize before rescaling. The minimum value is 600 seconds, which is also the default. The cooldown period starts when the model deployment becomes ACTIVE after the scaling operation.
    instance_count int
    (Updatable) The number of instances for the model deployment.
    is_enabled bool
    (Updatable) Whether the autoscaling policy is enabled.
    policyType String
    (Updatable) The type of scaling policy.
    autoScalingPolicies List<Property Map>
    (Updatable) The list of autoscaling policy details.
    coolDownInSeconds Number
    (Updatable) For threshold-based autoscaling policies, this value is the minimum period of time to wait between scaling actions. The cooldown period gives the system time to stabilize before rescaling. The minimum value is 600 seconds, which is also the default. The cooldown period starts when the model deployment becomes ACTIVE after the scaling operation.
    instanceCount Number
    (Updatable) The number of instances for the model deployment.
    isEnabled Boolean
    (Updatable) Whether the autoscaling policy is enabled.

    ModelDeploymentModelDeploymentConfigurationDetailsModelConfigurationDetailsScalingPolicyAutoScalingPolicy, ModelDeploymentModelDeploymentConfigurationDetailsModelConfigurationDetailsScalingPolicyAutoScalingPolicyArgs

    AutoScalingPolicyType string
    (Updatable) The type of autoscaling policy.
    InitialInstanceCount int
    (Updatable) For a threshold-based autoscaling policy, this value is the initial number of instances to launch in the model deployment immediately after autoscaling is enabled. Note that anytime this value is updated, the number of instances will be reset to this value. After autoscaling retrieves performance metrics, the number of instances is automatically adjusted from this initial number to a number that is based on the limits that you set.
    MaximumInstanceCount int
    (Updatable) For a threshold-based autoscaling policy, this value is the maximum number of instances the model deployment is allowed to increase to (scale out).
    MinimumInstanceCount int
    (Updatable) For a threshold-based autoscaling policy, this value is the minimum number of instances the model deployment is allowed to decrease to (scale in).
    Rules List<ModelDeploymentModelDeploymentConfigurationDetailsModelConfigurationDetailsScalingPolicyAutoScalingPolicyRule>
    (Updatable) The list of autoscaling policy rules.
    AutoScalingPolicyType string
    (Updatable) The type of autoscaling policy.
    InitialInstanceCount int
    (Updatable) For a threshold-based autoscaling policy, this value is the initial number of instances to launch in the model deployment immediately after autoscaling is enabled. Note that anytime this value is updated, the number of instances will be reset to this value. After autoscaling retrieves performance metrics, the number of instances is automatically adjusted from this initial number to a number that is based on the limits that you set.
    MaximumInstanceCount int
    (Updatable) For a threshold-based autoscaling policy, this value is the maximum number of instances the model deployment is allowed to increase to (scale out).
    MinimumInstanceCount int
    (Updatable) For a threshold-based autoscaling policy, this value is the minimum number of instances the model deployment is allowed to decrease to (scale in).
    Rules []ModelDeploymentModelDeploymentConfigurationDetailsModelConfigurationDetailsScalingPolicyAutoScalingPolicyRule
    (Updatable) The list of autoscaling policy rules.
    autoScalingPolicyType String
    (Updatable) The type of autoscaling policy.
    initialInstanceCount Integer
    (Updatable) For a threshold-based autoscaling policy, this value is the initial number of instances to launch in the model deployment immediately after autoscaling is enabled. Note that anytime this value is updated, the number of instances will be reset to this value. After autoscaling retrieves performance metrics, the number of instances is automatically adjusted from this initial number to a number that is based on the limits that you set.
    maximumInstanceCount Integer
    (Updatable) For a threshold-based autoscaling policy, this value is the maximum number of instances the model deployment is allowed to increase to (scale out).
    minimumInstanceCount Integer
    (Updatable) For a threshold-based autoscaling policy, this value is the minimum number of instances the model deployment is allowed to decrease to (scale in).
    rules List<ModelDeploymentModelDeploymentConfigurationDetailsModelConfigurationDetailsScalingPolicyAutoScalingPolicyRule>
    (Updatable) The list of autoscaling policy rules.
    autoScalingPolicyType string
    (Updatable) The type of autoscaling policy.
    initialInstanceCount number
    (Updatable) For a threshold-based autoscaling policy, this value is the initial number of instances to launch in the model deployment immediately after autoscaling is enabled. Note that anytime this value is updated, the number of instances will be reset to this value. After autoscaling retrieves performance metrics, the number of instances is automatically adjusted from this initial number to a number that is based on the limits that you set.
    maximumInstanceCount number
    (Updatable) For a threshold-based autoscaling policy, this value is the maximum number of instances the model deployment is allowed to increase to (scale out).
    minimumInstanceCount number
    (Updatable) For a threshold-based autoscaling policy, this value is the minimum number of instances the model deployment is allowed to decrease to (scale in).
    rules ModelDeploymentModelDeploymentConfigurationDetailsModelConfigurationDetailsScalingPolicyAutoScalingPolicyRule[]
    (Updatable) The list of autoscaling policy rules.
    auto_scaling_policy_type str
    (Updatable) The type of autoscaling policy.
    initial_instance_count int
    (Updatable) For a threshold-based autoscaling policy, this value is the initial number of instances to launch in the model deployment immediately after autoscaling is enabled. Note that anytime this value is updated, the number of instances will be reset to this value. After autoscaling retrieves performance metrics, the number of instances is automatically adjusted from this initial number to a number that is based on the limits that you set.
    maximum_instance_count int
    (Updatable) For a threshold-based autoscaling policy, this value is the maximum number of instances the model deployment is allowed to increase to (scale out).
    minimum_instance_count int
    (Updatable) For a threshold-based autoscaling policy, this value is the minimum number of instances the model deployment is allowed to decrease to (scale in).
    rules Sequence[datascience.ModelDeploymentModelDeploymentConfigurationDetailsModelConfigurationDetailsScalingPolicyAutoScalingPolicyRule]
    (Updatable) The list of autoscaling policy rules.
    autoScalingPolicyType String
    (Updatable) The type of autoscaling policy.
    initialInstanceCount Number
    (Updatable) For a threshold-based autoscaling policy, this value is the initial number of instances to launch in the model deployment immediately after autoscaling is enabled. Note that anytime this value is updated, the number of instances will be reset to this value. After autoscaling retrieves performance metrics, the number of instances is automatically adjusted from this initial number to a number that is based on the limits that you set.
    maximumInstanceCount Number
    (Updatable) For a threshold-based autoscaling policy, this value is the maximum number of instances the model deployment is allowed to increase to (scale out).
    minimumInstanceCount Number
    (Updatable) For a threshold-based autoscaling policy, this value is the minimum number of instances the model deployment is allowed to decrease to (scale in).
    rules List<Property Map>
    (Updatable) The list of autoscaling policy rules.

    ModelDeploymentModelDeploymentConfigurationDetailsModelConfigurationDetailsScalingPolicyAutoScalingPolicyRule, ModelDeploymentModelDeploymentConfigurationDetailsModelConfigurationDetailsScalingPolicyAutoScalingPolicyRuleArgs

    MetricExpressionRuleType string

    (Updatable) The metric expression for creating the alarm used to trigger autoscaling actions on the model deployment.

    The following values are supported:

    • PREDEFINED_EXPRESSION: An expression built using CPU or Memory metrics emitted by the Model Deployment Monitoring.
    • CUSTOM_EXPRESSION: A custom Monitoring Query Language (MQL) expression.
    ScaleInConfiguration ModelDeploymentModelDeploymentConfigurationDetailsModelConfigurationDetailsScalingPolicyAutoScalingPolicyRuleScaleInConfiguration
    (Updatable) The scaling configuration for the predefined metric expression rule.
    ScaleOutConfiguration ModelDeploymentModelDeploymentConfigurationDetailsModelConfigurationDetailsScalingPolicyAutoScalingPolicyRuleScaleOutConfiguration
    (Updatable) The scaling configuration for the predefined metric expression rule.
    MetricType string
    (Updatable) Metric type
    MetricExpressionRuleType string

    (Updatable) The metric expression for creating the alarm used to trigger autoscaling actions on the model deployment.

    The following values are supported:

    • PREDEFINED_EXPRESSION: An expression built using CPU or Memory metrics emitted by the Model Deployment Monitoring.
    • CUSTOM_EXPRESSION: A custom Monitoring Query Language (MQL) expression.
    ScaleInConfiguration ModelDeploymentModelDeploymentConfigurationDetailsModelConfigurationDetailsScalingPolicyAutoScalingPolicyRuleScaleInConfiguration
    (Updatable) The scaling configuration for the predefined metric expression rule.
    ScaleOutConfiguration ModelDeploymentModelDeploymentConfigurationDetailsModelConfigurationDetailsScalingPolicyAutoScalingPolicyRuleScaleOutConfiguration
    (Updatable) The scaling configuration for the predefined metric expression rule.
    MetricType string
    (Updatable) Metric type
    metricExpressionRuleType String

    (Updatable) The metric expression for creating the alarm used to trigger autoscaling actions on the model deployment.

    The following values are supported:

    • PREDEFINED_EXPRESSION: An expression built using CPU or Memory metrics emitted by the Model Deployment Monitoring.
    • CUSTOM_EXPRESSION: A custom Monitoring Query Language (MQL) expression.
    scaleInConfiguration ModelDeploymentModelDeploymentConfigurationDetailsModelConfigurationDetailsScalingPolicyAutoScalingPolicyRuleScaleInConfiguration
    (Updatable) The scaling configuration for the predefined metric expression rule.
    scaleOutConfiguration ModelDeploymentModelDeploymentConfigurationDetailsModelConfigurationDetailsScalingPolicyAutoScalingPolicyRuleScaleOutConfiguration
    (Updatable) The scaling configuration for the predefined metric expression rule.
    metricType String
    (Updatable) Metric type
    metricExpressionRuleType string

    (Updatable) The metric expression for creating the alarm used to trigger autoscaling actions on the model deployment.

    The following values are supported:

    • PREDEFINED_EXPRESSION: An expression built using CPU or Memory metrics emitted by the Model Deployment Monitoring.
    • CUSTOM_EXPRESSION: A custom Monitoring Query Language (MQL) expression.
    scaleInConfiguration ModelDeploymentModelDeploymentConfigurationDetailsModelConfigurationDetailsScalingPolicyAutoScalingPolicyRuleScaleInConfiguration
    (Updatable) The scaling configuration for the predefined metric expression rule.
    scaleOutConfiguration ModelDeploymentModelDeploymentConfigurationDetailsModelConfigurationDetailsScalingPolicyAutoScalingPolicyRuleScaleOutConfiguration
    (Updatable) The scaling configuration for the predefined metric expression rule.
    metricType string
    (Updatable) Metric type
    metric_expression_rule_type str

    (Updatable) The metric expression for creating the alarm used to trigger autoscaling actions on the model deployment.

    The following values are supported:

    • PREDEFINED_EXPRESSION: An expression built using CPU or Memory metrics emitted by the Model Deployment Monitoring.
    • CUSTOM_EXPRESSION: A custom Monitoring Query Language (MQL) expression.
    scale_in_configuration datascience.ModelDeploymentModelDeploymentConfigurationDetailsModelConfigurationDetailsScalingPolicyAutoScalingPolicyRuleScaleInConfiguration
    (Updatable) The scaling configuration for the predefined metric expression rule.
    scale_out_configuration datascience.ModelDeploymentModelDeploymentConfigurationDetailsModelConfigurationDetailsScalingPolicyAutoScalingPolicyRuleScaleOutConfiguration
    (Updatable) The scaling configuration for the predefined metric expression rule.
    metric_type str
    (Updatable) Metric type
    metricExpressionRuleType String

    (Updatable) The metric expression for creating the alarm used to trigger autoscaling actions on the model deployment.

    The following values are supported:

    • PREDEFINED_EXPRESSION: An expression built using CPU or Memory metrics emitted by the Model Deployment Monitoring.
    • CUSTOM_EXPRESSION: A custom Monitoring Query Language (MQL) expression.
    scaleInConfiguration Property Map
    (Updatable) The scaling configuration for the predefined metric expression rule.
    scaleOutConfiguration Property Map
    (Updatable) The scaling configuration for the predefined metric expression rule.
    metricType String
    (Updatable) Metric type

    ModelDeploymentModelDeploymentConfigurationDetailsModelConfigurationDetailsScalingPolicyAutoScalingPolicyRuleScaleInConfiguration, ModelDeploymentModelDeploymentConfigurationDetailsModelConfigurationDetailsScalingPolicyAutoScalingPolicyRuleScaleInConfigurationArgs

    InstanceCountAdjustment int
    (Updatable) The value is used for adjusting the count of instances by.
    PendingDuration string

    (Updatable) The period of time that the condition defined in the alarm must persist before the alarm state changes from "OK" to "FIRING" or vice versa. For example, a value of 5 minutes means that the alarm must persist in breaching the condition for five minutes before the alarm updates its state to "FIRING"; likewise, the alarm must persist in not breaching the condition for five minutes before the alarm updates its state to "OK."

    The duration is specified as a string in ISO 8601 format (PT10M for ten minutes or PT1H for one hour). Minimum: PT3M. Maximum: PT1H. Default: PT3M.

    Query string

    (Updatable) The Monitoring Query Language (MQL) expression to evaluate for the alarm. The Alarms feature of the Monitoring service interprets results for each returned time series as Boolean values, where zero represents false and a non-zero value represents true. A true value means that the trigger rule condition has been met. The query must specify a metric, statistic, interval, and trigger rule (threshold or absence). Supported values for interval: 1m-60m (also 1h). You can optionally specify dimensions and grouping functions. Supported grouping functions: grouping(), groupBy().

    Example of threshold alarm:


    CPUUtilization[1m]{resourceId = "MODEL_DEPLOYMENT_OCID"}.grouping().mean() < 25 CPUUtilization[1m]{resourceId = "MODEL_DEPLOYMENT_OCID"}.grouping().mean() > 75


    ScalingConfigurationType string
    (Updatable) The type of scaling configuration.
    Threshold int
    (Updatable) A metric value at which the scaling operation will be triggered.
    InstanceCountAdjustment int
    (Updatable) The value is used for adjusting the count of instances by.
    PendingDuration string

    (Updatable) The period of time that the condition defined in the alarm must persist before the alarm state changes from "OK" to "FIRING" or vice versa. For example, a value of 5 minutes means that the alarm must persist in breaching the condition for five minutes before the alarm updates its state to "FIRING"; likewise, the alarm must persist in not breaching the condition for five minutes before the alarm updates its state to "OK."

    The duration is specified as a string in ISO 8601 format (PT10M for ten minutes or PT1H for one hour). Minimum: PT3M. Maximum: PT1H. Default: PT3M.

    Query string

    (Updatable) The Monitoring Query Language (MQL) expression to evaluate for the alarm. The Alarms feature of the Monitoring service interprets results for each returned time series as Boolean values, where zero represents false and a non-zero value represents true. A true value means that the trigger rule condition has been met. The query must specify a metric, statistic, interval, and trigger rule (threshold or absence). Supported values for interval: 1m-60m (also 1h). You can optionally specify dimensions and grouping functions. Supported grouping functions: grouping(), groupBy().

    Example of threshold alarm:


    CPUUtilization[1m]{resourceId = "MODEL_DEPLOYMENT_OCID"}.grouping().mean() < 25 CPUUtilization[1m]{resourceId = "MODEL_DEPLOYMENT_OCID"}.grouping().mean() > 75


    ScalingConfigurationType string
    (Updatable) The type of scaling configuration.
    Threshold int
    (Updatable) A metric value at which the scaling operation will be triggered.
    instanceCountAdjustment Integer
    (Updatable) The value is used for adjusting the count of instances by.
    pendingDuration String

    (Updatable) The period of time that the condition defined in the alarm must persist before the alarm state changes from "OK" to "FIRING" or vice versa. For example, a value of 5 minutes means that the alarm must persist in breaching the condition for five minutes before the alarm updates its state to "FIRING"; likewise, the alarm must persist in not breaching the condition for five minutes before the alarm updates its state to "OK."

    The duration is specified as a string in ISO 8601 format (PT10M for ten minutes or PT1H for one hour). Minimum: PT3M. Maximum: PT1H. Default: PT3M.

    query String

    (Updatable) The Monitoring Query Language (MQL) expression to evaluate for the alarm. The Alarms feature of the Monitoring service interprets results for each returned time series as Boolean values, where zero represents false and a non-zero value represents true. A true value means that the trigger rule condition has been met. The query must specify a metric, statistic, interval, and trigger rule (threshold or absence). Supported values for interval: 1m-60m (also 1h). You can optionally specify dimensions and grouping functions. Supported grouping functions: grouping(), groupBy().

    Example of threshold alarm:


    CPUUtilization[1m]{resourceId = "MODEL_DEPLOYMENT_OCID"}.grouping().mean() < 25 CPUUtilization[1m]{resourceId = "MODEL_DEPLOYMENT_OCID"}.grouping().mean() > 75


    scalingConfigurationType String
    (Updatable) The type of scaling configuration.
    threshold Integer
    (Updatable) A metric value at which the scaling operation will be triggered.
    instanceCountAdjustment number
    (Updatable) The value is used for adjusting the count of instances by.
    pendingDuration string

    (Updatable) The period of time that the condition defined in the alarm must persist before the alarm state changes from "OK" to "FIRING" or vice versa. For example, a value of 5 minutes means that the alarm must persist in breaching the condition for five minutes before the alarm updates its state to "FIRING"; likewise, the alarm must persist in not breaching the condition for five minutes before the alarm updates its state to "OK."

    The duration is specified as a string in ISO 8601 format (PT10M for ten minutes or PT1H for one hour). Minimum: PT3M. Maximum: PT1H. Default: PT3M.

    query string

    (Updatable) The Monitoring Query Language (MQL) expression to evaluate for the alarm. The Alarms feature of the Monitoring service interprets results for each returned time series as Boolean values, where zero represents false and a non-zero value represents true. A true value means that the trigger rule condition has been met. The query must specify a metric, statistic, interval, and trigger rule (threshold or absence). Supported values for interval: 1m-60m (also 1h). You can optionally specify dimensions and grouping functions. Supported grouping functions: grouping(), groupBy().

    Example of threshold alarm:


    CPUUtilization[1m]{resourceId = "MODEL_DEPLOYMENT_OCID"}.grouping().mean() < 25 CPUUtilization[1m]{resourceId = "MODEL_DEPLOYMENT_OCID"}.grouping().mean() > 75


    scalingConfigurationType string
    (Updatable) The type of scaling configuration.
    threshold number
    (Updatable) A metric value at which the scaling operation will be triggered.
    instance_count_adjustment int
    (Updatable) The value is used for adjusting the count of instances by.
    pending_duration str

    (Updatable) The period of time that the condition defined in the alarm must persist before the alarm state changes from "OK" to "FIRING" or vice versa. For example, a value of 5 minutes means that the alarm must persist in breaching the condition for five minutes before the alarm updates its state to "FIRING"; likewise, the alarm must persist in not breaching the condition for five minutes before the alarm updates its state to "OK."

    The duration is specified as a string in ISO 8601 format (PT10M for ten minutes or PT1H for one hour). Minimum: PT3M. Maximum: PT1H. Default: PT3M.

    query str

    (Updatable) The Monitoring Query Language (MQL) expression to evaluate for the alarm. The Alarms feature of the Monitoring service interprets results for each returned time series as Boolean values, where zero represents false and a non-zero value represents true. A true value means that the trigger rule condition has been met. The query must specify a metric, statistic, interval, and trigger rule (threshold or absence). Supported values for interval: 1m-60m (also 1h). You can optionally specify dimensions and grouping functions. Supported grouping functions: grouping(), groupBy().

    Example of threshold alarm:


    CPUUtilization[1m]{resourceId = "MODEL_DEPLOYMENT_OCID"}.grouping().mean() < 25 CPUUtilization[1m]{resourceId = "MODEL_DEPLOYMENT_OCID"}.grouping().mean() > 75


    scaling_configuration_type str
    (Updatable) The type of scaling configuration.
    threshold int
    (Updatable) A metric value at which the scaling operation will be triggered.
    instanceCountAdjustment Number
    (Updatable) The value is used for adjusting the count of instances by.
    pendingDuration String

    (Updatable) The period of time that the condition defined in the alarm must persist before the alarm state changes from "OK" to "FIRING" or vice versa. For example, a value of 5 minutes means that the alarm must persist in breaching the condition for five minutes before the alarm updates its state to "FIRING"; likewise, the alarm must persist in not breaching the condition for five minutes before the alarm updates its state to "OK."

    The duration is specified as a string in ISO 8601 format (PT10M for ten minutes or PT1H for one hour). Minimum: PT3M. Maximum: PT1H. Default: PT3M.

    query String

    (Updatable) The Monitoring Query Language (MQL) expression to evaluate for the alarm. The Alarms feature of the Monitoring service interprets results for each returned time series as Boolean values, where zero represents false and a non-zero value represents true. A true value means that the trigger rule condition has been met. The query must specify a metric, statistic, interval, and trigger rule (threshold or absence). Supported values for interval: 1m-60m (also 1h). You can optionally specify dimensions and grouping functions. Supported grouping functions: grouping(), groupBy().

    Example of threshold alarm:


    CPUUtilization[1m]{resourceId = "MODEL_DEPLOYMENT_OCID"}.grouping().mean() < 25 CPUUtilization[1m]{resourceId = "MODEL_DEPLOYMENT_OCID"}.grouping().mean() > 75


    scalingConfigurationType String
    (Updatable) The type of scaling configuration.
    threshold Number
    (Updatable) A metric value at which the scaling operation will be triggered.

    ModelDeploymentModelDeploymentConfigurationDetailsModelConfigurationDetailsScalingPolicyAutoScalingPolicyRuleScaleOutConfiguration, ModelDeploymentModelDeploymentConfigurationDetailsModelConfigurationDetailsScalingPolicyAutoScalingPolicyRuleScaleOutConfigurationArgs

    InstanceCountAdjustment int
    (Updatable) The value is used for adjusting the count of instances by.
    PendingDuration string

    (Updatable) The period of time that the condition defined in the alarm must persist before the alarm state changes from "OK" to "FIRING" or vice versa. For example, a value of 5 minutes means that the alarm must persist in breaching the condition for five minutes before the alarm updates its state to "FIRING"; likewise, the alarm must persist in not breaching the condition for five minutes before the alarm updates its state to "OK."

    The duration is specified as a string in ISO 8601 format (PT10M for ten minutes or PT1H for one hour). Minimum: PT3M. Maximum: PT1H. Default: PT3M.

    Query string

    (Updatable) The Monitoring Query Language (MQL) expression to evaluate for the alarm. The Alarms feature of the Monitoring service interprets results for each returned time series as Boolean values, where zero represents false and a non-zero value represents true. A true value means that the trigger rule condition has been met. The query must specify a metric, statistic, interval, and trigger rule (threshold or absence). Supported values for interval: 1m-60m (also 1h). You can optionally specify dimensions and grouping functions. Supported grouping functions: grouping(), groupBy().

    Example of threshold alarm:


    CPUUtilization[1m]{resourceId = "MODEL_DEPLOYMENT_OCID"}.grouping().mean() < 25 CPUUtilization[1m]{resourceId = "MODEL_DEPLOYMENT_OCID"}.grouping().mean() > 75


    ScalingConfigurationType string
    (Updatable) The type of scaling configuration.
    Threshold int
    (Updatable) A metric value at which the scaling operation will be triggered.
    InstanceCountAdjustment int
    (Updatable) The value is used for adjusting the count of instances by.
    PendingDuration string

    (Updatable) The period of time that the condition defined in the alarm must persist before the alarm state changes from "OK" to "FIRING" or vice versa. For example, a value of 5 minutes means that the alarm must persist in breaching the condition for five minutes before the alarm updates its state to "FIRING"; likewise, the alarm must persist in not breaching the condition for five minutes before the alarm updates its state to "OK."

    The duration is specified as a string in ISO 8601 format (PT10M for ten minutes or PT1H for one hour). Minimum: PT3M. Maximum: PT1H. Default: PT3M.

    Query string

    (Updatable) The Monitoring Query Language (MQL) expression to evaluate for the alarm. The Alarms feature of the Monitoring service interprets results for each returned time series as Boolean values, where zero represents false and a non-zero value represents true. A true value means that the trigger rule condition has been met. The query must specify a metric, statistic, interval, and trigger rule (threshold or absence). Supported values for interval: 1m-60m (also 1h). You can optionally specify dimensions and grouping functions. Supported grouping functions: grouping(), groupBy().

    Example of threshold alarm:


    CPUUtilization[1m]{resourceId = "MODEL_DEPLOYMENT_OCID"}.grouping().mean() < 25 CPUUtilization[1m]{resourceId = "MODEL_DEPLOYMENT_OCID"}.grouping().mean() > 75


    ScalingConfigurationType string
    (Updatable) The type of scaling configuration.
    Threshold int
    (Updatable) A metric value at which the scaling operation will be triggered.
    instanceCountAdjustment Integer
    (Updatable) The value is used for adjusting the count of instances by.
    pendingDuration String

    (Updatable) The period of time that the condition defined in the alarm must persist before the alarm state changes from "OK" to "FIRING" or vice versa. For example, a value of 5 minutes means that the alarm must persist in breaching the condition for five minutes before the alarm updates its state to "FIRING"; likewise, the alarm must persist in not breaching the condition for five minutes before the alarm updates its state to "OK."

    The duration is specified as a string in ISO 8601 format (PT10M for ten minutes or PT1H for one hour). Minimum: PT3M. Maximum: PT1H. Default: PT3M.

    query String

    (Updatable) The Monitoring Query Language (MQL) expression to evaluate for the alarm. The Alarms feature of the Monitoring service interprets results for each returned time series as Boolean values, where zero represents false and a non-zero value represents true. A true value means that the trigger rule condition has been met. The query must specify a metric, statistic, interval, and trigger rule (threshold or absence). Supported values for interval: 1m-60m (also 1h). You can optionally specify dimensions and grouping functions. Supported grouping functions: grouping(), groupBy().

    Example of threshold alarm:


    CPUUtilization[1m]{resourceId = "MODEL_DEPLOYMENT_OCID"}.grouping().mean() < 25 CPUUtilization[1m]{resourceId = "MODEL_DEPLOYMENT_OCID"}.grouping().mean() > 75


    scalingConfigurationType String
    (Updatable) The type of scaling configuration.
    threshold Integer
    (Updatable) A metric value at which the scaling operation will be triggered.
    instanceCountAdjustment number
    (Updatable) The value is used for adjusting the count of instances by.
    pendingDuration string

    (Updatable) The period of time that the condition defined in the alarm must persist before the alarm state changes from "OK" to "FIRING" or vice versa. For example, a value of 5 minutes means that the alarm must persist in breaching the condition for five minutes before the alarm updates its state to "FIRING"; likewise, the alarm must persist in not breaching the condition for five minutes before the alarm updates its state to "OK."

    The duration is specified as a string in ISO 8601 format (PT10M for ten minutes or PT1H for one hour). Minimum: PT3M. Maximum: PT1H. Default: PT3M.

    query string

    (Updatable) The Monitoring Query Language (MQL) expression to evaluate for the alarm. The Alarms feature of the Monitoring service interprets results for each returned time series as Boolean values, where zero represents false and a non-zero value represents true. A true value means that the trigger rule condition has been met. The query must specify a metric, statistic, interval, and trigger rule (threshold or absence). Supported values for interval: 1m-60m (also 1h). You can optionally specify dimensions and grouping functions. Supported grouping functions: grouping(), groupBy().

    Example of threshold alarm:


    CPUUtilization[1m]{resourceId = "MODEL_DEPLOYMENT_OCID"}.grouping().mean() < 25 CPUUtilization[1m]{resourceId = "MODEL_DEPLOYMENT_OCID"}.grouping().mean() > 75


    scalingConfigurationType string
    (Updatable) The type of scaling configuration.
    threshold number
    (Updatable) A metric value at which the scaling operation will be triggered.
    instance_count_adjustment int
    (Updatable) The value is used for adjusting the count of instances by.
    pending_duration str

    (Updatable) The period of time that the condition defined in the alarm must persist before the alarm state changes from "OK" to "FIRING" or vice versa. For example, a value of 5 minutes means that the alarm must persist in breaching the condition for five minutes before the alarm updates its state to "FIRING"; likewise, the alarm must persist in not breaching the condition for five minutes before the alarm updates its state to "OK."

    The duration is specified as a string in ISO 8601 format (PT10M for ten minutes or PT1H for one hour). Minimum: PT3M. Maximum: PT1H. Default: PT3M.

    query str

    (Updatable) The Monitoring Query Language (MQL) expression to evaluate for the alarm. The Alarms feature of the Monitoring service interprets results for each returned time series as Boolean values, where zero represents false and a non-zero value represents true. A true value means that the trigger rule condition has been met. The query must specify a metric, statistic, interval, and trigger rule (threshold or absence). Supported values for interval: 1m-60m (also 1h). You can optionally specify dimensions and grouping functions. Supported grouping functions: grouping(), groupBy().

    Example of threshold alarm:


    CPUUtilization[1m]{resourceId = "MODEL_DEPLOYMENT_OCID"}.grouping().mean() < 25 CPUUtilization[1m]{resourceId = "MODEL_DEPLOYMENT_OCID"}.grouping().mean() > 75


    scaling_configuration_type str
    (Updatable) The type of scaling configuration.
    threshold int
    (Updatable) A metric value at which the scaling operation will be triggered.
    instanceCountAdjustment Number
    (Updatable) The value is used for adjusting the count of instances by.
    pendingDuration String

    (Updatable) The period of time that the condition defined in the alarm must persist before the alarm state changes from "OK" to "FIRING" or vice versa. For example, a value of 5 minutes means that the alarm must persist in breaching the condition for five minutes before the alarm updates its state to "FIRING"; likewise, the alarm must persist in not breaching the condition for five minutes before the alarm updates its state to "OK."

    The duration is specified as a string in ISO 8601 format (PT10M for ten minutes or PT1H for one hour). Minimum: PT3M. Maximum: PT1H. Default: PT3M.

    query String

    (Updatable) The Monitoring Query Language (MQL) expression to evaluate for the alarm. The Alarms feature of the Monitoring service interprets results for each returned time series as Boolean values, where zero represents false and a non-zero value represents true. A true value means that the trigger rule condition has been met. The query must specify a metric, statistic, interval, and trigger rule (threshold or absence). Supported values for interval: 1m-60m (also 1h). You can optionally specify dimensions and grouping functions. Supported grouping functions: grouping(), groupBy().

    Example of threshold alarm:


    CPUUtilization[1m]{resourceId = "MODEL_DEPLOYMENT_OCID"}.grouping().mean() < 25 CPUUtilization[1m]{resourceId = "MODEL_DEPLOYMENT_OCID"}.grouping().mean() > 75


    scalingConfigurationType String
    (Updatable) The type of scaling configuration.
    threshold Number
    (Updatable) A metric value at which the scaling operation will be triggered.

    ModelDeploymentModelDeploymentSystemData, ModelDeploymentModelDeploymentSystemDataArgs

    CurrentInstanceCount int
    This value is the current count of the model deployment instances.
    SystemInfraType string
    The infrastructure type of the model deployment.
    CurrentInstanceCount int
    This value is the current count of the model deployment instances.
    SystemInfraType string
    The infrastructure type of the model deployment.
    currentInstanceCount Integer
    This value is the current count of the model deployment instances.
    systemInfraType String
    The infrastructure type of the model deployment.
    currentInstanceCount number
    This value is the current count of the model deployment instances.
    systemInfraType string
    The infrastructure type of the model deployment.
    current_instance_count int
    This value is the current count of the model deployment instances.
    system_infra_type str
    The infrastructure type of the model deployment.
    currentInstanceCount Number
    This value is the current count of the model deployment instances.
    systemInfraType String
    The infrastructure type of the model deployment.

    Import

    ModelDeployments can be imported using the id, e.g.

    $ pulumi import oci:DataScience/modelDeployment:ModelDeployment test_model_deployment "id"
    

    To learn more about importing existing cloud resources, see Importing resources.

    Package Details

    Repository
    oci pulumi/pulumi-oci
    License
    Apache-2.0
    Notes
    This Pulumi package is based on the oci Terraform Provider.
    oci logo
    Oracle Cloud Infrastructure v1.41.0 published on Wednesday, Jun 19, 2024 by Pulumi