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Viewing docs for DataRobot v0.11.3
published on Wednesday, Sep 9, 2026 by DataRobot, Inc.
Schema (JSON)
datarobot-community/pulumi-datarobot

datarobot.CustomMetric

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Viewing docs for DataRobot v0.11.3
published on Wednesday, Sep 9, 2026 by DataRobot, Inc.
Schema (JSON)
datarobot-community/pulumi-datarobot

    Custom Metric

    Example Usage

    import * as pulumi from "@pulumi/pulumi";
import * as datarobot from "@datarobot/pulumi-datarobot";

const example = new datarobot.CustomModel("example", {
    name: "Example Custom Model",
    targetType: "Binary",
    targetName: "my_label",
    baseEnvironmentId: "65f9b27eab986d30d4c64268",
    files: ["example.py"],
});
const exampleRegisteredModel = new datarobot.RegisteredModel("example", {
    customModelVersionId: example.versionId,
    name: "Example Registered Model",
});
const examplePredictionEnvironment = new datarobot.PredictionEnvironment("example", {
    name: "Example Prediction Environment",
    platform: "datarobotServerless",
});
const exampleDeployment = new datarobot.Deployment("example", {
    label: "An example deployment",
    predictionEnvironmentId: examplePredictionEnvironment.id,
    registeredModelVersionId: exampleRegisteredModel.versionId,
});
const exampleCustomMetric = new datarobot.CustomMetric("example", {
    deploymentId: exampleDeployment.id,
    name: "example custom metric",
    description: "example description",
    units: "dollars",
    directionality: "higherIsBetter",
    type: "sum",
    baselineValue: 0.5,
    isModelSpecific: true,
    isGeospatial: false,
    timeStep: "hour",
    timestamp: {
        columnName: "timestamp_column",
        timeFormat: "%Y-%m-%dT%H:%M:%SZ",
    },
    value: {
        columnName: "value_column",
    },
    batch: {
        columnName: "batch_column",
    },
    sampleCount: {
        columnName: "sample_count_column",
    },
    associationId: {
        columnName: "association_id_column",
    },
});
export const exampleId = exampleCustomMetric.id;

    import pulumi
import pulumi_datarobot as datarobot

example = datarobot.CustomModel("example",
    name="Example Custom Model",
    target_type="Binary",
    target_name="my_label",
    base_environment_id="65f9b27eab986d30d4c64268",
    files=["example.py"])
example_registered_model = datarobot.RegisteredModel("example",
    custom_model_version_id=example.version_id,
    name="Example Registered Model")
example_prediction_environment = datarobot.PredictionEnvironment("example",
    name="Example Prediction Environment",
    platform="datarobotServerless")
example_deployment = datarobot.Deployment("example",
    label="An example deployment",
    prediction_environment_id=example_prediction_environment.id,
    registered_model_version_id=example_registered_model.version_id)
example_custom_metric = datarobot.CustomMetric("example",
    deployment_id=example_deployment.id,
    name="example custom metric",
    description="example description",
    units="dollars",
    directionality="higherIsBetter",
    type="sum",
    baseline_value=0.5,
    is_model_specific=True,
    is_geospatial=False,
    time_step="hour",
    timestamp={
        "column_name": "timestamp_column",
        "time_format": "%Y-%m-%dT%H:%M:%SZ",
    },
    value={
        "column_name": "value_column",
    },
    batch={
        "column_name": "batch_column",
    },
    sample_count={
        "column_name": "sample_count_column",
    },
    association_id={
        "columnName": "association_id_column",
    })
pulumi.export("exampleId", example_custom_metric.id)

    package main

import (
	"github.com/datarobot-community/pulumi-datarobot/sdk/go/datarobot"
	"github.com/pulumi/pulumi/sdk/v3/go/pulumi"
)

func main() {
	pulumi.Run(func(ctx *pulumi.Context) error {
		example, err := datarobot.NewCustomModel(ctx, "example", &datarobot.CustomModelArgs{
			Name:              pulumi.String("Example Custom Model"),
			TargetType:        pulumi.String("Binary"),
			TargetName:        pulumi.String("my_label"),
			BaseEnvironmentId: pulumi.String("65f9b27eab986d30d4c64268"),
			Files: pulumi.Any{
				"example.py",
			},
		})
		if err != nil {
			return err
		}
		exampleRegisteredModel, err := datarobot.NewRegisteredModel(ctx, "example", &datarobot.RegisteredModelArgs{
			CustomModelVersionId: example.VersionId,
			Name:                 pulumi.String("Example Registered Model"),
		})
		if err != nil {
			return err
		}
		examplePredictionEnvironment, err := datarobot.NewPredictionEnvironment(ctx, "example", &datarobot.PredictionEnvironmentArgs{
			Name:     pulumi.String("Example Prediction Environment"),
			Platform: pulumi.String("datarobotServerless"),
		})
		if err != nil {
			return err
		}
		exampleDeployment, err := datarobot.NewDeployment(ctx, "example", &datarobot.DeploymentArgs{
			Label:                    pulumi.String("An example deployment"),
			PredictionEnvironmentId:  examplePredictionEnvironment.ID().ToIDOutput().ToStringOutput(),
			RegisteredModelVersionId: exampleRegisteredModel.VersionId,
		})
		if err != nil {
			return err
		}
		exampleCustomMetric, err := datarobot.NewCustomMetric(ctx, "example", &datarobot.CustomMetricArgs{
			DeploymentId:    exampleDeployment.ID().ToIDOutput().ToStringOutput(),
			Name:            pulumi.String("example custom metric"),
			Description:     pulumi.String("example description"),
			Units:           pulumi.String("dollars"),
			Directionality:  pulumi.String("higherIsBetter"),
			Type:            pulumi.String("sum"),
			BaselineValue:   pulumi.Float64(0.5),
			IsModelSpecific: pulumi.Bool(true),
			IsGeospatial:    pulumi.Bool(false),
			TimeStep:        "hour",
			Timestamp: &datarobot.CustomMetricTimestampArgs{
				ColumnName: pulumi.String("timestamp_column"),
				TimeFormat: pulumi.String("%Y-%m-%dT%H:%M:%SZ"),
			},
			Value: &datarobot.CustomMetricValueArgs{
				ColumnName: pulumi.String("value_column"),
			},
			Batch: &datarobot.CustomMetricBatchArgs{
				ColumnName: pulumi.String("batch_column"),
			},
			SampleCount: &datarobot.CustomMetricSampleCountArgs{
				ColumnName: pulumi.String("sample_count_column"),
			},
			AssociationId: map[string]string{
				"columnName": "association_id_column",
			},
		})
		if err != nil {
			return err
		}
		ctx.Export("exampleId", exampleCustomMetric.ID())
		return nil
	})
}

    using System.Collections.Generic;
using System.Linq;
using Pulumi;
using Datarobot = DataRobotPulumi.Datarobot;

return await Deployment.RunAsync(() => 
{
    var example = new Datarobot.CustomModel("example", new()
    {
        Name = "Example Custom Model",
        TargetType = "Binary",
        TargetName = "my_label",
        BaseEnvironmentId = "65f9b27eab986d30d4c64268",
        Files = new[]
        {
            "example.py",
        },
    });

    var exampleRegisteredModel = new Datarobot.RegisteredModel("example", new()
    {
        CustomModelVersionId = example.VersionId,
        Name = "Example Registered Model",
    });

    var examplePredictionEnvironment = new Datarobot.PredictionEnvironment("example", new()
    {
        Name = "Example Prediction Environment",
        Platform = "datarobotServerless",
    });

    var exampleDeployment = new Datarobot.Deployment("example", new()
    {
        Label = "An example deployment",
        PredictionEnvironmentId = examplePredictionEnvironment.Id,
        RegisteredModelVersionId = exampleRegisteredModel.VersionId,
    });

    var exampleCustomMetric = new Datarobot.CustomMetric("example", new()
    {
        DeploymentId = exampleDeployment.Id,
        Name = "example custom metric",
        Description = "example description",
        Units = "dollars",
        Directionality = "higherIsBetter",
        Type = "sum",
        BaselineValue = 0.5,
        IsModelSpecific = true,
        IsGeospatial = false,
        TimeStep = "hour",
        Timestamp = new Datarobot.Inputs.CustomMetricTimestampArgs
        {
            ColumnName = "timestamp_column",
            TimeFormat = "%Y-%m-%dT%H:%M:%SZ",
        },
        Value = new Datarobot.Inputs.CustomMetricValueArgs
        {
            ColumnName = "value_column",
        },
        Batch = new Datarobot.Inputs.CustomMetricBatchArgs
        {
            ColumnName = "batch_column",
        },
        SampleCount = new Datarobot.Inputs.CustomMetricSampleCountArgs
        {
            ColumnName = "sample_count_column",
        },
        AssociationId = 
        {
            { "columnName", "association_id_column" },
        },
    });

    return new Dictionary<string, object?>
    {
        ["exampleId"] = exampleCustomMetric.Id,
    };
});

    package generated_program;

import com.pulumi.Context;
import com.pulumi.Pulumi;
import com.pulumi.core.Output;
import com.pulumi.datarobot.CustomModel;
import com.pulumi.datarobot.CustomModelArgs;
import com.pulumi.datarobot.RegisteredModel;
import com.pulumi.datarobot.RegisteredModelArgs;
import com.pulumi.datarobot.PredictionEnvironment;
import com.pulumi.datarobot.PredictionEnvironmentArgs;
import com.pulumi.datarobot.Deployment;
import com.pulumi.datarobot.DeploymentArgs;
import com.pulumi.datarobot.CustomMetric;
import com.pulumi.datarobot.CustomMetricArgs;
import com.pulumi.datarobot.inputs.CustomMetricTimestampArgs;
import com.pulumi.datarobot.inputs.CustomMetricValueArgs;
import com.pulumi.datarobot.inputs.CustomMetricBatchArgs;
import com.pulumi.datarobot.inputs.CustomMetricSampleCountArgs;
import java.util.ArrayList;
import java.util.Arrays;
import java.util.Map;
import java.io.File;
import java.nio.file.Files;
import java.nio.file.Paths;

public class App {
    public static void main(String[] args) {
        Pulumi.run(App::stack);
    }

    public static void stack(Context ctx) {
        var example = new CustomModel("example", CustomModelArgs.builder()
            .name("Example Custom Model")
            .targetType("Binary")
            .targetName("my_label")
            .baseEnvironmentId("65f9b27eab986d30d4c64268")
            .files("example.py")
            .build());

        var exampleRegisteredModel = new RegisteredModel("exampleRegisteredModel", RegisteredModelArgs.builder()
            .customModelVersionId(example.versionId())
            .name("Example Registered Model")
            .build());

        var examplePredictionEnvironment = new PredictionEnvironment("examplePredictionEnvironment", PredictionEnvironmentArgs.builder()
            .name("Example Prediction Environment")
            .platform("datarobotServerless")
            .build());

        var exampleDeployment = new Deployment("exampleDeployment", DeploymentArgs.builder()
            .label("An example deployment")
            .predictionEnvironmentId(examplePredictionEnvironment.id())
            .registeredModelVersionId(exampleRegisteredModel.versionId())
            .build());

        var exampleCustomMetric = new CustomMetric("exampleCustomMetric", CustomMetricArgs.builder()
            .deploymentId(exampleDeployment.id())
            .name("example custom metric")
            .description("example description")
            .units("dollars")
            .directionality("higherIsBetter")
            .type("sum")
            .baselineValue(0.5)
            .isModelSpecific(true)
            .isGeospatial(false)
            .timeStep("hour")
            .timestamp(CustomMetricTimestampArgs.builder()
                .columnName("timestamp_column")
                .timeFormat("%Y-%m-%dT%H:%M:%SZ")
                .build())
            .value(CustomMetricValueArgs.builder()
                .columnName("value_column")
                .build())
            .batch(CustomMetricBatchArgs.builder()
                .columnName("batch_column")
                .build())
            .sampleCount(CustomMetricSampleCountArgs.builder()
                .columnName("sample_count_column")
                .build())
            .associationId(Map.of("columnName", "association_id_column"))
            .build());

        ctx.export("exampleId", exampleCustomMetric.id());
    }
}

    resources:
  example:
    type: datarobot:CustomModel
    properties:
      name: Example Custom Model
      targetType: Binary
      targetName: my_label
      baseEnvironmentId: 65f9b27eab986d30d4c64268
      files:
        - example.py
  exampleRegisteredModel:
    type: datarobot:RegisteredModel
    name: example
    properties:
      customModelVersionId: ${example.versionId}
      name: Example Registered Model
  examplePredictionEnvironment:
    type: datarobot:PredictionEnvironment
    name: example
    properties:
      name: Example Prediction Environment
      platform: datarobotServerless
  exampleDeployment:
    type: datarobot:Deployment
    name: example
    properties:
      label: An example deployment
      predictionEnvironmentId: ${examplePredictionEnvironment.id}
      registeredModelVersionId: ${exampleRegisteredModel.versionId}
  exampleCustomMetric:
    type: datarobot:CustomMetric
    name: example
    properties:
      deploymentId: ${exampleDeployment.id}
      name: example custom metric
      description: example description
      units: dollars
      directionality: higherIsBetter
      type: sum
      baselineValue: 0.5
      isModelSpecific: true
      isGeospatial: false # Optional
      timeStep: hour
      timestamp:
        columnName: timestamp_column
        timeFormat: '%Y-%m-%dT%H:%M:%SZ'
      value:
        columnName: value_column
      batch:
        columnName: batch_column
      sampleCount:
        columnName: sample_count_column
      associationId:
        columnName: association_id_column
outputs:
  exampleId: ${exampleCustomMetric.id}

    pulumi {
  required_providers {
    datarobot = {
      source = "pulumi/datarobot"
    }
  }
}

resource "datarobot_custommodel" "example" {
  name                = "Example Custom Model"
  target_type         = "Binary"
  target_name         = "my_label"
  base_environment_id = "65f9b27eab986d30d4c64268"
  files               = ["example.py"]
}
resource "datarobot_registeredmodel" "example" {
  custom_model_version_id = datarobot_custommodel.example.version_id
  name                    = "Example Registered Model"
}
resource "datarobot_predictionenvironment" "example" {
  name     = "Example Prediction Environment"
  platform = "datarobotServerless"
}
resource "datarobot_deployment" "example" {
  label                       = "An example deployment"
  prediction_environment_id   = datarobot_predictionenvironment.example.id
  registered_model_version_id = datarobot_registeredmodel.example.version_id
}
resource "datarobot_custommetric" "example" {
  deployment_id     = datarobot_deployment.example.id
  name              = "example custom metric"
  description       = "example description"
  units             = "dollars"
  directionality    = "higherIsBetter"
  type              = "sum"
  baseline_value    = 0.5
  is_model_specific = true
  is_geospatial     = false
  # Optional
  time_step = "hour"
  timestamp = {
    column_name = "timestamp_column"
    time_format = "%Y-%m-%dT%H:%M:%SZ"
  }
  value = {
    column_name = "value_column"
  }
  batch = {
    column_name = "batch_column"
  }
  sample_count = {
    column_name = "sample_count_column"
  }
  association_id = {
    "columnName" = "association_id_column"
  }
}
output "exampleId" {
  value = datarobot_custommetric.example.id
}

    Create CustomMetric Resource

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

    Constructor syntax

    new CustomMetric(name: string, args: CustomMetricArgs, opts?: CustomResourceOptions);
    @overload
def CustomMetric(resource_name: str,
                 args: CustomMetricArgs,
                 opts: Optional[ResourceOptions] = None)

@overload
def CustomMetric(resource_name: str,
                 opts: Optional[ResourceOptions] = None,
                 is_model_specific: Optional[bool] = None,
                 units: Optional[str] = None,
                 deployment_id: Optional[str] = None,
                 type: Optional[str] = None,
                 directionality: Optional[str] = None,
                 is_geospatial: Optional[bool] = None,
                 description: Optional[str] = None,
                 name: Optional[str] = None,
                 sample_count: Optional[CustomMetricSampleCountArgs] = None,
                 timestamp: Optional[CustomMetricTimestampArgs] = None,
                 baseline_value: Optional[float] = None,
                 batch: Optional[CustomMetricBatchArgs] = None,
                 value: Optional[CustomMetricValueArgs] = None)
    func NewCustomMetric(ctx *Context, name string, args CustomMetricArgs, opts ...ResourceOption) (*CustomMetric, error)
    public CustomMetric(string name, CustomMetricArgs args, CustomResourceOptions? opts = null)
    public CustomMetric(String name, CustomMetricArgs args)
public CustomMetric(String name, CustomMetricArgs args, CustomResourceOptions options)

    type: datarobot:CustomMetric
properties: # The arguments to resource properties.
options: # Bag of options to control resource's behavior.


    resource "datarobot_custom_metric" "name" {
    # resource properties
}

    Parameters

    name string
    The unique name of the resource.
    args CustomMetricArgs
    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 CustomMetricArgs
    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 CustomMetricArgs
    The arguments to resource properties.
    opts ResourceOption
    Bag of options to control resource's behavior.
    name string
    The unique name of the resource.
    args CustomMetricArgs
    The arguments to resource properties.
    opts CustomResourceOptions
    Bag of options to control resource's behavior.
    name String
    The unique name of the resource.
    args CustomMetricArgs
    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 customMetricResource = new Datarobot.CustomMetric("customMetricResource", new()
{
    IsModelSpecific = false,
    Units = "string",
    DeploymentId = "string",
    Type = "string",
    Directionality = "string",
    IsGeospatial = false,
    Description = "string",
    Name = "string",
    SampleCount = new Datarobot.Inputs.CustomMetricSampleCountArgs
    {
        ColumnName = "string",
    },
    Timestamp = new Datarobot.Inputs.CustomMetricTimestampArgs
    {
        ColumnName = "string",
        TimeFormat = "string",
    },
    BaselineValue = 0.0,
    Batch = new Datarobot.Inputs.CustomMetricBatchArgs
    {
        ColumnName = "string",
    },
    Value = new Datarobot.Inputs.CustomMetricValueArgs
    {
        ColumnName = "string",
    },
});

    example, err := datarobot.NewCustomMetric(ctx, "customMetricResource", &datarobot.CustomMetricArgs{
	IsModelSpecific: pulumi.Bool(false),
	Units:           pulumi.String("string"),
	DeploymentId:    pulumi.String("string"),
	Type:            pulumi.String("string"),
	Directionality:  pulumi.String("string"),
	IsGeospatial:    pulumi.Bool(false),
	Description:     pulumi.String("string"),
	Name:            pulumi.String("string"),
	SampleCount: &datarobot.CustomMetricSampleCountArgs{
		ColumnName: pulumi.String("string"),
	},
	Timestamp: &datarobot.CustomMetricTimestampArgs{
		ColumnName: pulumi.String("string"),
		TimeFormat: pulumi.String("string"),
	},
	BaselineValue: pulumi.Float64(0),
	Batch: &datarobot.CustomMetricBatchArgs{
		ColumnName: pulumi.String("string"),
	},
	Value: &datarobot.CustomMetricValueArgs{
		ColumnName: pulumi.String("string"),
	},
})

    resource "datarobot_custom_metric" "customMetricResource" {
  lifecycle {
    create_before_destroy = true
  }
  is_model_specific = false
  units             = "string"
  deployment_id     = "string"
  type              = "string"
  directionality    = "string"
  is_geospatial     = false
  description       = "string"
  name              = "string"
  sample_count = {
    column_name = "string"
  }
  timestamp = {
    column_name = "string"
    time_format = "string"
  }
  baseline_value = 0
  batch = {
    column_name = "string"
  }
  value = {
    column_name = "string"
  }
}

    var customMetricResource = new CustomMetric("customMetricResource", CustomMetricArgs.builder()
    .isModelSpecific(false)
    .units("string")
    .deploymentId("string")
    .type("string")
    .directionality("string")
    .isGeospatial(false)
    .description("string")
    .name("string")
    .sampleCount(CustomMetricSampleCountArgs.builder()
        .columnName("string")
        .build())
    .timestamp(CustomMetricTimestampArgs.builder()
        .columnName("string")
        .timeFormat("string")
        .build())
    .baselineValue(0.0)
    .batch(CustomMetricBatchArgs.builder()
        .columnName("string")
        .build())
    .value(CustomMetricValueArgs.builder()
        .columnName("string")
        .build())
    .build());

    custom_metric_resource = datarobot.CustomMetric("customMetricResource",
    is_model_specific=False,
    units="string",
    deployment_id="string",
    type="string",
    directionality="string",
    is_geospatial=False,
    description="string",
    name="string",
    sample_count={
        "column_name": "string",
    },
    timestamp={
        "column_name": "string",
        "time_format": "string",
    },
    baseline_value=float(0),
    batch={
        "column_name": "string",
    },
    value={
        "column_name": "string",
    })

    const customMetricResource = new datarobot.CustomMetric("customMetricResource", {
    isModelSpecific: false,
    units: "string",
    deploymentId: "string",
    type: "string",
    directionality: "string",
    isGeospatial: false,
    description: "string",
    name: "string",
    sampleCount: {
        columnName: "string",
    },
    timestamp: {
        columnName: "string",
        timeFormat: "string",
    },
    baselineValue: 0,
    batch: {
        columnName: "string",
    },
    value: {
        columnName: "string",
    },
});

    type: datarobot:CustomMetric
properties:
    baselineValue: 0
    batch:
        columnName: string
    deploymentId: string
    description: string
    directionality: string
    isGeospatial: false
    isModelSpecific: false
    name: string
    sampleCount:
        columnName: string
    timestamp:
        columnName: string
        timeFormat: string
    type: string
    units: string
    value:
        columnName: string

    CustomMetric Resource Properties

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

    Inputs

    In Python, inputs that are objects can be passed either as argument classes or as dictionary literals.

    The CustomMetric resource accepts the following input properties:

    DeploymentId string
    ID of the Deployment for the Custom Metric.
    Directionality string
    Directionality of the Custom Metric
    IsGeospatial bool
    Determines whether the metric is geospatial.
    IsModelSpecific bool
    Determines whether the metric is related to the model or deployment.
    Type string
    Aggregation type of the Custom Metric.
    Units string
    The units, or the y-axis label, of the given Custom Metric.
    BaselineValue double
    The baseline value used to add “reference dots” to the values over time chart.
    Batch DataRobotCustomMetricBatch
    A Custom Metric batch ID source when reading values from columnar dataset.
    Description string
    Description of the Custom Metric.
    Name string
    Name of the Custom Metric.
    SampleCount DataRobotCustomMetricSampleCount
    A Custom Metric sample source when reading values from columnar dataset.
    Timestamp DataRobotCustomMetricTimestamp
    A Custom Metric timestamp column source when reading values from columnar dataset.
    Value DataRobotCustomMetricValue
    A Custom Metric value source when reading values from columnar dataset.
    DeploymentId string
    ID of the Deployment for the Custom Metric.
    Directionality string
    Directionality of the Custom Metric
    IsGeospatial bool
    Determines whether the metric is geospatial.
    IsModelSpecific bool
    Determines whether the metric is related to the model or deployment.
    Type string
    Aggregation type of the Custom Metric.
    Units string
    The units, or the y-axis label, of the given Custom Metric.
    BaselineValue float64
    The baseline value used to add “reference dots” to the values over time chart.
    Batch CustomMetricBatchArgs
    A Custom Metric batch ID source when reading values from columnar dataset.
    Description string
    Description of the Custom Metric.
    Name string
    Name of the Custom Metric.
    SampleCount CustomMetricSampleCountArgs
    A Custom Metric sample source when reading values from columnar dataset.
    Timestamp CustomMetricTimestampArgs
    A Custom Metric timestamp column source when reading values from columnar dataset.
    Value CustomMetricValueArgs
    A Custom Metric value source when reading values from columnar dataset.
    deployment_id string
    ID of the Deployment for the Custom Metric.
    directionality string
    Directionality of the Custom Metric
    is_geospatial bool
    Determines whether the metric is geospatial.
    is_model_specific bool
    Determines whether the metric is related to the model or deployment.
    type string
    Aggregation type of the Custom Metric.
    units string
    The units, or the y-axis label, of the given Custom Metric.
    baseline_value number
    The baseline value used to add “reference dots” to the values over time chart.
    batch object
    A Custom Metric batch ID source when reading values from columnar dataset.
    description string
    Description of the Custom Metric.
    name string
    Name of the Custom Metric.
    sample_count object
    A Custom Metric sample source when reading values from columnar dataset.
    timestamp object
    A Custom Metric timestamp column source when reading values from columnar dataset.
    value object
    A Custom Metric value source when reading values from columnar dataset.
    deploymentId String
    ID of the Deployment for the Custom Metric.
    directionality String
    Directionality of the Custom Metric
    isGeospatial Boolean
    Determines whether the metric is geospatial.
    isModelSpecific Boolean
    Determines whether the metric is related to the model or deployment.
    type String
    Aggregation type of the Custom Metric.
    units String
    The units, or the y-axis label, of the given Custom Metric.
    baselineValue Double
    The baseline value used to add “reference dots” to the values over time chart.
    batch CustomMetricBatch
    A Custom Metric batch ID source when reading values from columnar dataset.
    description String
    Description of the Custom Metric.
    name String
    Name of the Custom Metric.
    sampleCount CustomMetricSampleCount
    A Custom Metric sample source when reading values from columnar dataset.
    timestamp CustomMetricTimestamp
    A Custom Metric timestamp column source when reading values from columnar dataset.
    value CustomMetricValue
    A Custom Metric value source when reading values from columnar dataset.
    deploymentId string
    ID of the Deployment for the Custom Metric.
    directionality string
    Directionality of the Custom Metric
    isGeospatial boolean
    Determines whether the metric is geospatial.
    isModelSpecific boolean
    Determines whether the metric is related to the model or deployment.
    type string
    Aggregation type of the Custom Metric.
    units string
    The units, or the y-axis label, of the given Custom Metric.
    baselineValue number
    The baseline value used to add “reference dots” to the values over time chart.
    batch CustomMetricBatch
    A Custom Metric batch ID source when reading values from columnar dataset.
    description string
    Description of the Custom Metric.
    name string
    Name of the Custom Metric.
    sampleCount CustomMetricSampleCount
    A Custom Metric sample source when reading values from columnar dataset.
    timestamp CustomMetricTimestamp
    A Custom Metric timestamp column source when reading values from columnar dataset.
    value CustomMetricValue
    A Custom Metric value source when reading values from columnar dataset.
    deployment_id str
    ID of the Deployment for the Custom Metric.
    directionality str
    Directionality of the Custom Metric
    is_geospatial bool
    Determines whether the metric is geospatial.
    is_model_specific bool
    Determines whether the metric is related to the model or deployment.
    type str
    Aggregation type of the Custom Metric.
    units str
    The units, or the y-axis label, of the given Custom Metric.
    baseline_value float
    The baseline value used to add “reference dots” to the values over time chart.
    batch CustomMetricBatchArgs
    A Custom Metric batch ID source when reading values from columnar dataset.
    description str
    Description of the Custom Metric.
    name str
    Name of the Custom Metric.
    sample_count CustomMetricSampleCountArgs
    A Custom Metric sample source when reading values from columnar dataset.
    timestamp CustomMetricTimestampArgs
    A Custom Metric timestamp column source when reading values from columnar dataset.
    value CustomMetricValueArgs
    A Custom Metric value source when reading values from columnar dataset.
    deploymentId String
    ID of the Deployment for the Custom Metric.
    directionality String
    Directionality of the Custom Metric
    isGeospatial Boolean
    Determines whether the metric is geospatial.
    isModelSpecific Boolean
    Determines whether the metric is related to the model or deployment.
    type String
    Aggregation type of the Custom Metric.
    units String
    The units, or the y-axis label, of the given Custom Metric.
    baselineValue Number
    The baseline value used to add “reference dots” to the values over time chart.
    batch Property Map
    A Custom Metric batch ID source when reading values from columnar dataset.
    description String
    Description of the Custom Metric.
    name String
    Name of the Custom Metric.
    sampleCount Property Map
    A Custom Metric sample source when reading values from columnar dataset.
    timestamp Property Map
    A Custom Metric timestamp column source when reading values from columnar dataset.
    value Property Map
    A Custom Metric value source when reading values from columnar dataset.

    Outputs

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

    Id string
    The provider-assigned unique ID for this managed resource.
    Id string
    The provider-assigned unique ID for this managed resource.
    id string
    The provider-assigned unique ID for this managed resource.
    id String
    The provider-assigned unique ID for this managed resource.
    id string
    The provider-assigned unique ID for this managed resource.
    id str
    The provider-assigned unique ID for this managed resource.
    id String
    The provider-assigned unique ID for this managed resource.

    Look up Existing CustomMetric Resource

    Get an existing CustomMetric 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?: CustomMetricState, opts?: CustomResourceOptions): CustomMetric
    @staticmethod
def get(resource_name: str,
        id: str,
        opts: Optional[ResourceOptions] = None,
        baseline_value: Optional[float] = None,
        batch: Optional[CustomMetricBatchArgs] = None,
        deployment_id: Optional[str] = None,
        description: Optional[str] = None,
        directionality: Optional[str] = None,
        is_geospatial: Optional[bool] = None,
        is_model_specific: Optional[bool] = None,
        name: Optional[str] = None,
        sample_count: Optional[CustomMetricSampleCountArgs] = None,
        timestamp: Optional[CustomMetricTimestampArgs] = None,
        type: Optional[str] = None,
        units: Optional[str] = None,
        value: Optional[CustomMetricValueArgs] = None) -> CustomMetric
    func GetCustomMetric(ctx *Context, name string, id IDInput, state *CustomMetricState, opts ...ResourceOption) (*CustomMetric, error)
    public static CustomMetric Get(string name, Input<string> id, CustomMetricState? state, CustomResourceOptions? opts = null)
    public static CustomMetric get(String name, Output<String> id, CustomMetricState state, CustomResourceOptions options)
    resources:  _:    type: datarobot:CustomMetric    get:      id: ${id}
    import {
  to = datarobot_custom_metric.example
  id = "${id}"
}
    name
    The unique name of the resulting resource.
    id
    The unique provider ID of the resource to lookup.
    state
    Any extra arguments used during the lookup.
    opts
    A bag of options that control this resource's behavior.
    resource_name
    The unique name of the resulting resource.
    id
    The unique provider ID of the resource to lookup.
    name
    The unique name of the resulting resource.
    id
    The unique provider ID of the resource to lookup.
    state
    Any extra arguments used during the lookup.
    opts
    A bag of options that control this resource's behavior.
    name
    The unique name of the resulting resource.
    id
    The unique provider ID of the resource to lookup.
    state
    Any extra arguments used during the lookup.
    opts
    A bag of options that control this resource's behavior.
    name
    The unique name of the resulting resource.
    id
    The unique provider ID of the resource to lookup.
    state
    Any extra arguments used during the lookup.
    opts
    A bag of options that control this resource's behavior.
    The following state arguments are supported:
    BaselineValue double
    The baseline value used to add “reference dots” to the values over time chart.
    Batch DataRobotCustomMetricBatch
    A Custom Metric batch ID source when reading values from columnar dataset.
    DeploymentId string
    ID of the Deployment for the Custom Metric.
    Description string
    Description of the Custom Metric.
    Directionality string
    Directionality of the Custom Metric
    IsGeospatial bool
    Determines whether the metric is geospatial.
    IsModelSpecific bool
    Determines whether the metric is related to the model or deployment.
    Name string
    Name of the Custom Metric.
    SampleCount DataRobotCustomMetricSampleCount
    A Custom Metric sample source when reading values from columnar dataset.
    Timestamp DataRobotCustomMetricTimestamp
    A Custom Metric timestamp column source when reading values from columnar dataset.
    Type string
    Aggregation type of the Custom Metric.
    Units string
    The units, or the y-axis label, of the given Custom Metric.
    Value DataRobotCustomMetricValue
    A Custom Metric value source when reading values from columnar dataset.
    BaselineValue float64
    The baseline value used to add “reference dots” to the values over time chart.
    Batch CustomMetricBatchArgs
    A Custom Metric batch ID source when reading values from columnar dataset.
    DeploymentId string
    ID of the Deployment for the Custom Metric.
    Description string
    Description of the Custom Metric.
    Directionality string
    Directionality of the Custom Metric
    IsGeospatial bool
    Determines whether the metric is geospatial.
    IsModelSpecific bool
    Determines whether the metric is related to the model or deployment.
    Name string
    Name of the Custom Metric.
    SampleCount CustomMetricSampleCountArgs
    A Custom Metric sample source when reading values from columnar dataset.
    Timestamp CustomMetricTimestampArgs
    A Custom Metric timestamp column source when reading values from columnar dataset.
    Type string
    Aggregation type of the Custom Metric.
    Units string
    The units, or the y-axis label, of the given Custom Metric.
    Value CustomMetricValueArgs
    A Custom Metric value source when reading values from columnar dataset.
    baseline_value number
    The baseline value used to add “reference dots” to the values over time chart.
    batch object
    A Custom Metric batch ID source when reading values from columnar dataset.
    deployment_id string
    ID of the Deployment for the Custom Metric.
    description string
    Description of the Custom Metric.
    directionality string
    Directionality of the Custom Metric
    is_geospatial bool
    Determines whether the metric is geospatial.
    is_model_specific bool
    Determines whether the metric is related to the model or deployment.
    name string
    Name of the Custom Metric.
    sample_count object
    A Custom Metric sample source when reading values from columnar dataset.
    timestamp object
    A Custom Metric timestamp column source when reading values from columnar dataset.
    type string
    Aggregation type of the Custom Metric.
    units string
    The units, or the y-axis label, of the given Custom Metric.
    value object
    A Custom Metric value source when reading values from columnar dataset.
    baselineValue Double
    The baseline value used to add “reference dots” to the values over time chart.
    batch CustomMetricBatch
    A Custom Metric batch ID source when reading values from columnar dataset.
    deploymentId String
    ID of the Deployment for the Custom Metric.
    description String
    Description of the Custom Metric.
    directionality String
    Directionality of the Custom Metric
    isGeospatial Boolean
    Determines whether the metric is geospatial.
    isModelSpecific Boolean
    Determines whether the metric is related to the model or deployment.
    name String
    Name of the Custom Metric.
    sampleCount CustomMetricSampleCount
    A Custom Metric sample source when reading values from columnar dataset.
    timestamp CustomMetricTimestamp
    A Custom Metric timestamp column source when reading values from columnar dataset.
    type String
    Aggregation type of the Custom Metric.
    units String
    The units, or the y-axis label, of the given Custom Metric.
    value CustomMetricValue
    A Custom Metric value source when reading values from columnar dataset.
    baselineValue number
    The baseline value used to add “reference dots” to the values over time chart.
    batch CustomMetricBatch
    A Custom Metric batch ID source when reading values from columnar dataset.
    deploymentId string
    ID of the Deployment for the Custom Metric.
    description string
    Description of the Custom Metric.
    directionality string
    Directionality of the Custom Metric
    isGeospatial boolean
    Determines whether the metric is geospatial.
    isModelSpecific boolean
    Determines whether the metric is related to the model or deployment.
    name string
    Name of the Custom Metric.
    sampleCount CustomMetricSampleCount
    A Custom Metric sample source when reading values from columnar dataset.
    timestamp CustomMetricTimestamp
    A Custom Metric timestamp column source when reading values from columnar dataset.
    type string
    Aggregation type of the Custom Metric.
    units string
    The units, or the y-axis label, of the given Custom Metric.
    value CustomMetricValue
    A Custom Metric value source when reading values from columnar dataset.
    baseline_value float
    The baseline value used to add “reference dots” to the values over time chart.
    batch CustomMetricBatchArgs
    A Custom Metric batch ID source when reading values from columnar dataset.
    deployment_id str
    ID of the Deployment for the Custom Metric.
    description str
    Description of the Custom Metric.
    directionality str
    Directionality of the Custom Metric
    is_geospatial bool
    Determines whether the metric is geospatial.
    is_model_specific bool
    Determines whether the metric is related to the model or deployment.
    name str
    Name of the Custom Metric.
    sample_count CustomMetricSampleCountArgs
    A Custom Metric sample source when reading values from columnar dataset.
    timestamp CustomMetricTimestampArgs
    A Custom Metric timestamp column source when reading values from columnar dataset.
    type str
    Aggregation type of the Custom Metric.
    units str
    The units, or the y-axis label, of the given Custom Metric.
    value CustomMetricValueArgs
    A Custom Metric value source when reading values from columnar dataset.
    baselineValue Number
    The baseline value used to add “reference dots” to the values over time chart.
    batch Property Map
    A Custom Metric batch ID source when reading values from columnar dataset.
    deploymentId String
    ID of the Deployment for the Custom Metric.
    description String
    Description of the Custom Metric.
    directionality String
    Directionality of the Custom Metric
    isGeospatial Boolean
    Determines whether the metric is geospatial.
    isModelSpecific Boolean
    Determines whether the metric is related to the model or deployment.
    name String
    Name of the Custom Metric.
    sampleCount Property Map
    A Custom Metric sample source when reading values from columnar dataset.
    timestamp Property Map
    A Custom Metric timestamp column source when reading values from columnar dataset.
    type String
    Aggregation type of the Custom Metric.
    units String
    The units, or the y-axis label, of the given Custom Metric.
    value Property Map
    A Custom Metric value source when reading values from columnar dataset.

    Supporting Types

    CustomMetricBatch, CustomMetricBatchArgs

    ColumnName string
    Column name.
    ColumnName string
    Column name.
    column_name string
    Column name.
    columnName String
    Column name.
    columnName string
    Column name.
    column_name str
    Column name.
    columnName String
    Column name.

    CustomMetricSampleCount, CustomMetricSampleCountArgs

    ColumnName string
    Column name.
    ColumnName string
    Column name.
    column_name string
    Column name.
    columnName String
    Column name.
    columnName string
    Column name.
    column_name str
    Column name.
    columnName String
    Column name.

    CustomMetricTimestamp, CustomMetricTimestampArgs

    ColumnName string
    Column name.
    TimeFormat string
    Format.
    ColumnName string
    Column name.
    TimeFormat string
    Format.
    column_name string
    Column name.
    time_format string
    Format.
    columnName String
    Column name.
    timeFormat String
    Format.
    columnName string
    Column name.
    timeFormat string
    Format.
    column_name str
    Column name.
    time_format str
    Format.
    columnName String
    Column name.
    timeFormat String
    Format.

    CustomMetricValue, CustomMetricValueArgs

    ColumnName string
    Column name.
    ColumnName string
    Column name.
    column_name string
    Column name.
    columnName String
    Column name.
    columnName string
    Column name.
    column_name str
    Column name.
    columnName String
    Column name.

    Package Details

    Repository
    datarobot datarobot-community/pulumi-datarobot
    License
    Apache-2.0
    Notes
    This Pulumi package is based on the datarobot Terraform Provider.
    datarobot logo
    Viewing docs for DataRobot v0.11.3
    published on Wednesday, Sep 9, 2026 by DataRobot, Inc.
    Schema (JSON)
    datarobot-community/pulumi-datarobot

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