Docs Home Pulumi IaC Pulumi ESC Pulumi Cloud Packages Tutorials
  1. Packages
  2. DataRobot
  3. API Docs
  4. DeploymentRetrainingPolicy
DataRobot v0.8.16 published on Tuesday, Mar 18, 2025 by DataRobot, Inc.
datarobot-community/pulumi-datarobot

datarobot.DeploymentRetrainingPolicy

Explore with Pulumi AI

datarobot logo
DataRobot v0.8.16 published on Tuesday, Mar 18, 2025 by DataRobot, Inc.
datarobot-community/pulumi-datarobot

    Deployment Retraining Policy

    Example Usage

    Coming soon!

    Coming soon!

    Coming soon!

    Coming soon!

    package generated_program;

import com.pulumi.Context;
import com.pulumi.Pulumi;
import com.pulumi.core.Output;
import com.pulumi.datarobot.DeploymentRetrainingPolicy;
import com.pulumi.datarobot.DeploymentRetrainingPolicyArgs;
import com.pulumi.datarobot.inputs.DeploymentRetrainingPolicyTriggerArgs;
import com.pulumi.datarobot.inputs.DeploymentRetrainingPolicyAutopilotOptionsArgs;
import com.pulumi.datarobot.inputs.DeploymentRetrainingPolicyProjectOptionsArgs;
import com.pulumi.datarobot.inputs.DeploymentRetrainingPolicyTimeSeriesOptionsArgs;
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 example = new DeploymentRetrainingPolicy("example", DeploymentRetrainingPolicyArgs.builder()
            .deploymentId(datarobot_deployment.example().id())
            .description("Example Description")
            .action("create_model_package")
            .modelSelectionStrategy("custom_job")
            .featureListStrategy("informative_features")
            .projectOptionsStrategy("custom")
            .trigger(DeploymentRetrainingPolicyTriggerArgs.builder()
                .custom_job_id(datarobot_custom_job.example().id())
                .build())
            .autopilotOptions()
            .projectOptions()
            .timeSeriesOptions()
            .build());

        ctx.export("datarobotDeploymentRetrainingPolicyId", example.id());
    }
}

    resources:
  example:
    type: datarobot:DeploymentRetrainingPolicy
    properties:
      deploymentId: ${datarobot_deployment.example.id}
      description: Example Description
      # Optional
      action: create_model_package
      modelSelectionStrategy: custom_job
      featureListStrategy: informative_features
      projectOptionsStrategy: custom
      trigger:
        custom_job_id: ${datarobot_custom_job.example.id}
      autopilotOptions: {}
      projectOptions: {}
      timeSeriesOptions: {}
outputs:
  datarobotDeploymentRetrainingPolicyId: ${example.id}

    Create DeploymentRetrainingPolicy Resource

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

    Constructor syntax

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

@overload
def DeploymentRetrainingPolicy(resource_name: str,
                               opts: Optional[ResourceOptions] = None,
                               deployment_id: Optional[str] = None,
                               description: Optional[str] = None,
                               action: Optional[str] = None,
                               autopilot_options: Optional[DeploymentRetrainingPolicyAutopilotOptionsArgs] = None,
                               feature_list_strategy: Optional[str] = None,
                               model_selection_strategy: Optional[str] = None,
                               name: Optional[str] = None,
                               project_options: Optional[DeploymentRetrainingPolicyProjectOptionsArgs] = None,
                               project_options_strategy: Optional[str] = None,
                               time_series_options: Optional[DeploymentRetrainingPolicyTimeSeriesOptionsArgs] = None,
                               trigger: Optional[DeploymentRetrainingPolicyTriggerArgs] = None)
    func NewDeploymentRetrainingPolicy(ctx *Context, name string, args DeploymentRetrainingPolicyArgs, opts ...ResourceOption) (*DeploymentRetrainingPolicy, error)
    public DeploymentRetrainingPolicy(string name, DeploymentRetrainingPolicyArgs args, CustomResourceOptions? opts = null)
    public DeploymentRetrainingPolicy(String name, DeploymentRetrainingPolicyArgs args)
public DeploymentRetrainingPolicy(String name, DeploymentRetrainingPolicyArgs args, CustomResourceOptions options)

    type: datarobot:DeploymentRetrainingPolicy
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 DeploymentRetrainingPolicyArgs
    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 DeploymentRetrainingPolicyArgs
    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 DeploymentRetrainingPolicyArgs
    The arguments to resource properties.
    opts ResourceOption
    Bag of options to control resource's behavior.
    name string
    The unique name of the resource.
    args DeploymentRetrainingPolicyArgs
    The arguments to resource properties.
    opts CustomResourceOptions
    Bag of options to control resource's behavior.
    name String
    The unique name of the resource.
    args DeploymentRetrainingPolicyArgs
    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 deploymentRetrainingPolicyResource = new Datarobot.DeploymentRetrainingPolicy("deploymentRetrainingPolicyResource", new()
{
    DeploymentId = "string",
    Description = "string",
    Action = "string",
    AutopilotOptions = new Datarobot.Inputs.DeploymentRetrainingPolicyAutopilotOptionsArgs
    {
        BlendBestModels = false,
        Mode = "string",
        RunLeakageRemovedFeatureList = false,
        ScoringCodeOnly = false,
        ShapOnlyMode = false,
    },
    FeatureListStrategy = "string",
    ModelSelectionStrategy = "string",
    Name = "string",
    ProjectOptions = new Datarobot.Inputs.DeploymentRetrainingPolicyProjectOptionsArgs
    {
        CvMethod = "string",
        HoldoutPct = 0,
        Metric = "string",
        Reps = 0,
        ValidationPct = 0,
        ValidationType = "string",
    },
    ProjectOptionsStrategy = "string",
    TimeSeriesOptions = new Datarobot.Inputs.DeploymentRetrainingPolicyTimeSeriesOptionsArgs
    {
        CalendarId = "string",
        DifferencingMethod = "string",
        ExponentiallyWeightedMovingAlpha = 0,
        Periodicities = new[]
        {
            new Datarobot.Inputs.DeploymentRetrainingPolicyTimeSeriesOptionsPeriodicityArgs
            {
                TimeSteps = 0,
                TimeUnit = "string",
            },
        },
        TreatAsExponential = "string",
    },
    Trigger = new Datarobot.Inputs.DeploymentRetrainingPolicyTriggerArgs
    {
        CustomJobId = "string",
        MinIntervalBetweenRuns = "string",
        Schedule = new Datarobot.Inputs.DeploymentRetrainingPolicyTriggerScheduleArgs
        {
            DayOfMonths = new[]
            {
                "string",
            },
            DayOfWeeks = new[]
            {
                "string",
            },
            Hours = new[]
            {
                "string",
            },
            Minutes = new[]
            {
                "string",
            },
            Months = new[]
            {
                "string",
            },
        },
        StatusDeclinesToFailing = false,
        StatusDeclinesToWarning = false,
        StatusStillInDecline = false,
        Type = "string",
    },
});

    example, err := datarobot.NewDeploymentRetrainingPolicy(ctx, "deploymentRetrainingPolicyResource", &datarobot.DeploymentRetrainingPolicyArgs{
	DeploymentId: pulumi.String("string"),
	Description:  pulumi.String("string"),
	Action:       pulumi.String("string"),
	AutopilotOptions: &datarobot.DeploymentRetrainingPolicyAutopilotOptionsArgs{
		BlendBestModels:              pulumi.Bool(false),
		Mode:                         pulumi.String("string"),
		RunLeakageRemovedFeatureList: pulumi.Bool(false),
		ScoringCodeOnly:              pulumi.Bool(false),
		ShapOnlyMode:                 pulumi.Bool(false),
	},
	FeatureListStrategy:    pulumi.String("string"),
	ModelSelectionStrategy: pulumi.String("string"),
	Name:                   pulumi.String("string"),
	ProjectOptions: &datarobot.DeploymentRetrainingPolicyProjectOptionsArgs{
		CvMethod:       pulumi.String("string"),
		HoldoutPct:     pulumi.Float64(0),
		Metric:         pulumi.String("string"),
		Reps:           pulumi.Float64(0),
		ValidationPct:  pulumi.Float64(0),
		ValidationType: pulumi.String("string"),
	},
	ProjectOptionsStrategy: pulumi.String("string"),
	TimeSeriesOptions: &datarobot.DeploymentRetrainingPolicyTimeSeriesOptionsArgs{
		CalendarId:                       pulumi.String("string"),
		DifferencingMethod:               pulumi.String("string"),
		ExponentiallyWeightedMovingAlpha: pulumi.Float64(0),
		Periodicities: datarobot.DeploymentRetrainingPolicyTimeSeriesOptionsPeriodicityArray{
			&datarobot.DeploymentRetrainingPolicyTimeSeriesOptionsPeriodicityArgs{
				TimeSteps: pulumi.Int(0),
				TimeUnit:  pulumi.String("string"),
			},
		},
		TreatAsExponential: pulumi.String("string"),
	},
	Trigger: &datarobot.DeploymentRetrainingPolicyTriggerArgs{
		CustomJobId:            pulumi.String("string"),
		MinIntervalBetweenRuns: pulumi.String("string"),
		Schedule: &datarobot.DeploymentRetrainingPolicyTriggerScheduleArgs{
			DayOfMonths: pulumi.StringArray{
				pulumi.String("string"),
			},
			DayOfWeeks: pulumi.StringArray{
				pulumi.String("string"),
			},
			Hours: pulumi.StringArray{
				pulumi.String("string"),
			},
			Minutes: pulumi.StringArray{
				pulumi.String("string"),
			},
			Months: pulumi.StringArray{
				pulumi.String("string"),
			},
		},
		StatusDeclinesToFailing: pulumi.Bool(false),
		StatusDeclinesToWarning: pulumi.Bool(false),
		StatusStillInDecline:    pulumi.Bool(false),
		Type:                    pulumi.String("string"),
	},
})

    var deploymentRetrainingPolicyResource = new DeploymentRetrainingPolicy("deploymentRetrainingPolicyResource", DeploymentRetrainingPolicyArgs.builder()
    .deploymentId("string")
    .description("string")
    .action("string")
    .autopilotOptions(DeploymentRetrainingPolicyAutopilotOptionsArgs.builder()
        .blendBestModels(false)
        .mode("string")
        .runLeakageRemovedFeatureList(false)
        .scoringCodeOnly(false)
        .shapOnlyMode(false)
        .build())
    .featureListStrategy("string")
    .modelSelectionStrategy("string")
    .name("string")
    .projectOptions(DeploymentRetrainingPolicyProjectOptionsArgs.builder()
        .cvMethod("string")
        .holdoutPct(0)
        .metric("string")
        .reps(0)
        .validationPct(0)
        .validationType("string")
        .build())
    .projectOptionsStrategy("string")
    .timeSeriesOptions(DeploymentRetrainingPolicyTimeSeriesOptionsArgs.builder()
        .calendarId("string")
        .differencingMethod("string")
        .exponentiallyWeightedMovingAlpha(0)
        .periodicities(DeploymentRetrainingPolicyTimeSeriesOptionsPeriodicityArgs.builder()
            .timeSteps(0)
            .timeUnit("string")
            .build())
        .treatAsExponential("string")
        .build())
    .trigger(DeploymentRetrainingPolicyTriggerArgs.builder()
        .customJobId("string")
        .minIntervalBetweenRuns("string")
        .schedule(DeploymentRetrainingPolicyTriggerScheduleArgs.builder()
            .dayOfMonths("string")
            .dayOfWeeks("string")
            .hours("string")
            .minutes("string")
            .months("string")
            .build())
        .statusDeclinesToFailing(false)
        .statusDeclinesToWarning(false)
        .statusStillInDecline(false)
        .type("string")
        .build())
    .build());

    deployment_retraining_policy_resource = datarobot.DeploymentRetrainingPolicy("deploymentRetrainingPolicyResource",
    deployment_id="string",
    description="string",
    action="string",
    autopilot_options={
        "blend_best_models": False,
        "mode": "string",
        "run_leakage_removed_feature_list": False,
        "scoring_code_only": False,
        "shap_only_mode": False,
    },
    feature_list_strategy="string",
    model_selection_strategy="string",
    name="string",
    project_options={
        "cv_method": "string",
        "holdout_pct": 0,
        "metric": "string",
        "reps": 0,
        "validation_pct": 0,
        "validation_type": "string",
    },
    project_options_strategy="string",
    time_series_options={
        "calendar_id": "string",
        "differencing_method": "string",
        "exponentially_weighted_moving_alpha": 0,
        "periodicities": [{
            "time_steps": 0,
            "time_unit": "string",
        }],
        "treat_as_exponential": "string",
    },
    trigger={
        "custom_job_id": "string",
        "min_interval_between_runs": "string",
        "schedule": {
            "day_of_months": ["string"],
            "day_of_weeks": ["string"],
            "hours": ["string"],
            "minutes": ["string"],
            "months": ["string"],
        },
        "status_declines_to_failing": False,
        "status_declines_to_warning": False,
        "status_still_in_decline": False,
        "type": "string",
    })

    const deploymentRetrainingPolicyResource = new datarobot.DeploymentRetrainingPolicy("deploymentRetrainingPolicyResource", {
    deploymentId: "string",
    description: "string",
    action: "string",
    autopilotOptions: {
        blendBestModels: false,
        mode: "string",
        runLeakageRemovedFeatureList: false,
        scoringCodeOnly: false,
        shapOnlyMode: false,
    },
    featureListStrategy: "string",
    modelSelectionStrategy: "string",
    name: "string",
    projectOptions: {
        cvMethod: "string",
        holdoutPct: 0,
        metric: "string",
        reps: 0,
        validationPct: 0,
        validationType: "string",
    },
    projectOptionsStrategy: "string",
    timeSeriesOptions: {
        calendarId: "string",
        differencingMethod: "string",
        exponentiallyWeightedMovingAlpha: 0,
        periodicities: [{
            timeSteps: 0,
            timeUnit: "string",
        }],
        treatAsExponential: "string",
    },
    trigger: {
        customJobId: "string",
        minIntervalBetweenRuns: "string",
        schedule: {
            dayOfMonths: ["string"],
            dayOfWeeks: ["string"],
            hours: ["string"],
            minutes: ["string"],
            months: ["string"],
        },
        statusDeclinesToFailing: false,
        statusDeclinesToWarning: false,
        statusStillInDecline: false,
        type: "string",
    },
});

    type: datarobot:DeploymentRetrainingPolicy
properties:
    action: string
    autopilotOptions:
        blendBestModels: false
        mode: string
        runLeakageRemovedFeatureList: false
        scoringCodeOnly: false
        shapOnlyMode: false
    deploymentId: string
    description: string
    featureListStrategy: string
    modelSelectionStrategy: string
    name: string
    projectOptions:
        cvMethod: string
        holdoutPct: 0
        metric: string
        reps: 0
        validationPct: 0
        validationType: string
    projectOptionsStrategy: string
    timeSeriesOptions:
        calendarId: string
        differencingMethod: string
        exponentiallyWeightedMovingAlpha: 0
        periodicities:
            - timeSteps: 0
              timeUnit: string
        treatAsExponential: string
    trigger:
        customJobId: string
        minIntervalBetweenRuns: string
        schedule:
            dayOfMonths:
                - string
            dayOfWeeks:
                - string
            hours:
                - string
            minutes:
                - string
            months:
                - string
        statusDeclinesToFailing: false
        statusDeclinesToWarning: false
        statusStillInDecline: false
        type: string

    DeploymentRetrainingPolicy 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 DeploymentRetrainingPolicy resource accepts the following input properties:

    DeploymentId string
    The ID of the Deployment for the Retraining Policy.
    Description string
    The description of the Retraining Policy.
    Action string
    The the action to take on the resultant new model.
    AutopilotOptions DataRobotDeploymentRetrainingPolicyAutopilotOptions
    Options for projects used to build new models.
    FeatureListStrategy string
    The feature list strategy used for modeling.
    ModelSelectionStrategy string
    Determines how the new model is selected when the retraining policy runs.
    Name string
    The name of the Retraining Policy.
    ProjectOptions DataRobotDeploymentRetrainingPolicyProjectOptions
    Options for projects used to build new models.
    ProjectOptionsStrategy string
    The project option strategy used for modeling.
    TimeSeriesOptions DataRobotDeploymentRetrainingPolicyTimeSeriesOptions
    Time Series project options used to build new models.
    Trigger DataRobotDeploymentRetrainingPolicyTrigger
    Retraining policy trigger.
    DeploymentId string
    The ID of the Deployment for the Retraining Policy.
    Description string
    The description of the Retraining Policy.
    Action string
    The the action to take on the resultant new model.
    AutopilotOptions DeploymentRetrainingPolicyAutopilotOptionsArgs
    Options for projects used to build new models.
    FeatureListStrategy string
    The feature list strategy used for modeling.
    ModelSelectionStrategy string
    Determines how the new model is selected when the retraining policy runs.
    Name string
    The name of the Retraining Policy.
    ProjectOptions DeploymentRetrainingPolicyProjectOptionsArgs
    Options for projects used to build new models.
    ProjectOptionsStrategy string
    The project option strategy used for modeling.
    TimeSeriesOptions DeploymentRetrainingPolicyTimeSeriesOptionsArgs
    Time Series project options used to build new models.
    Trigger DeploymentRetrainingPolicyTriggerArgs
    Retraining policy trigger.
    deploymentId String
    The ID of the Deployment for the Retraining Policy.
    description String
    The description of the Retraining Policy.
    action String
    The the action to take on the resultant new model.
    autopilotOptions DeploymentRetrainingPolicyAutopilotOptions
    Options for projects used to build new models.
    featureListStrategy String
    The feature list strategy used for modeling.
    modelSelectionStrategy String
    Determines how the new model is selected when the retraining policy runs.
    name String
    The name of the Retraining Policy.
    projectOptions DeploymentRetrainingPolicyProjectOptions
    Options for projects used to build new models.
    projectOptionsStrategy String
    The project option strategy used for modeling.
    timeSeriesOptions DeploymentRetrainingPolicyTimeSeriesOptions
    Time Series project options used to build new models.
    trigger DeploymentRetrainingPolicyTrigger
    Retraining policy trigger.
    deploymentId string
    The ID of the Deployment for the Retraining Policy.
    description string
    The description of the Retraining Policy.
    action string
    The the action to take on the resultant new model.
    autopilotOptions DeploymentRetrainingPolicyAutopilotOptions
    Options for projects used to build new models.
    featureListStrategy string
    The feature list strategy used for modeling.
    modelSelectionStrategy string
    Determines how the new model is selected when the retraining policy runs.
    name string
    The name of the Retraining Policy.
    projectOptions DeploymentRetrainingPolicyProjectOptions
    Options for projects used to build new models.
    projectOptionsStrategy string
    The project option strategy used for modeling.
    timeSeriesOptions DeploymentRetrainingPolicyTimeSeriesOptions
    Time Series project options used to build new models.
    trigger DeploymentRetrainingPolicyTrigger
    Retraining policy trigger.
    deployment_id str
    The ID of the Deployment for the Retraining Policy.
    description str
    The description of the Retraining Policy.
    action str
    The the action to take on the resultant new model.
    autopilot_options DeploymentRetrainingPolicyAutopilotOptionsArgs
    Options for projects used to build new models.
    feature_list_strategy str
    The feature list strategy used for modeling.
    model_selection_strategy str
    Determines how the new model is selected when the retraining policy runs.
    name str
    The name of the Retraining Policy.
    project_options DeploymentRetrainingPolicyProjectOptionsArgs
    Options for projects used to build new models.
    project_options_strategy str
    The project option strategy used for modeling.
    time_series_options DeploymentRetrainingPolicyTimeSeriesOptionsArgs
    Time Series project options used to build new models.
    trigger DeploymentRetrainingPolicyTriggerArgs
    Retraining policy trigger.
    deploymentId String
    The ID of the Deployment for the Retraining Policy.
    description String
    The description of the Retraining Policy.
    action String
    The the action to take on the resultant new model.
    autopilotOptions Property Map
    Options for projects used to build new models.
    featureListStrategy String
    The feature list strategy used for modeling.
    modelSelectionStrategy String
    Determines how the new model is selected when the retraining policy runs.
    name String
    The name of the Retraining Policy.
    projectOptions Property Map
    Options for projects used to build new models.
    projectOptionsStrategy String
    The project option strategy used for modeling.
    timeSeriesOptions Property Map
    Time Series project options used to build new models.
    trigger Property Map
    Retraining policy trigger.

    Outputs

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

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

    Look up Existing DeploymentRetrainingPolicy Resource

    Get an existing DeploymentRetrainingPolicy 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?: DeploymentRetrainingPolicyState, opts?: CustomResourceOptions): DeploymentRetrainingPolicy
    @staticmethod
def get(resource_name: str,
        id: str,
        opts: Optional[ResourceOptions] = None,
        action: Optional[str] = None,
        autopilot_options: Optional[DeploymentRetrainingPolicyAutopilotOptionsArgs] = None,
        deployment_id: Optional[str] = None,
        description: Optional[str] = None,
        feature_list_strategy: Optional[str] = None,
        model_selection_strategy: Optional[str] = None,
        name: Optional[str] = None,
        project_options: Optional[DeploymentRetrainingPolicyProjectOptionsArgs] = None,
        project_options_strategy: Optional[str] = None,
        time_series_options: Optional[DeploymentRetrainingPolicyTimeSeriesOptionsArgs] = None,
        trigger: Optional[DeploymentRetrainingPolicyTriggerArgs] = None) -> DeploymentRetrainingPolicy
    func GetDeploymentRetrainingPolicy(ctx *Context, name string, id IDInput, state *DeploymentRetrainingPolicyState, opts ...ResourceOption) (*DeploymentRetrainingPolicy, error)
    public static DeploymentRetrainingPolicy Get(string name, Input<string> id, DeploymentRetrainingPolicyState? state, CustomResourceOptions? opts = null)
    public static DeploymentRetrainingPolicy get(String name, Output<String> id, DeploymentRetrainingPolicyState state, CustomResourceOptions options)
    resources:  _:    type: datarobot:DeploymentRetrainingPolicy    get:      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:
    Action string
    The the action to take on the resultant new model.
    AutopilotOptions DataRobotDeploymentRetrainingPolicyAutopilotOptions
    Options for projects used to build new models.
    DeploymentId string
    The ID of the Deployment for the Retraining Policy.
    Description string
    The description of the Retraining Policy.
    FeatureListStrategy string
    The feature list strategy used for modeling.
    ModelSelectionStrategy string
    Determines how the new model is selected when the retraining policy runs.
    Name string
    The name of the Retraining Policy.
    ProjectOptions DataRobotDeploymentRetrainingPolicyProjectOptions
    Options for projects used to build new models.
    ProjectOptionsStrategy string
    The project option strategy used for modeling.
    TimeSeriesOptions DataRobotDeploymentRetrainingPolicyTimeSeriesOptions
    Time Series project options used to build new models.
    Trigger DataRobotDeploymentRetrainingPolicyTrigger
    Retraining policy trigger.
    Action string
    The the action to take on the resultant new model.
    AutopilotOptions DeploymentRetrainingPolicyAutopilotOptionsArgs
    Options for projects used to build new models.
    DeploymentId string
    The ID of the Deployment for the Retraining Policy.
    Description string
    The description of the Retraining Policy.
    FeatureListStrategy string
    The feature list strategy used for modeling.
    ModelSelectionStrategy string
    Determines how the new model is selected when the retraining policy runs.
    Name string
    The name of the Retraining Policy.
    ProjectOptions DeploymentRetrainingPolicyProjectOptionsArgs
    Options for projects used to build new models.
    ProjectOptionsStrategy string
    The project option strategy used for modeling.
    TimeSeriesOptions DeploymentRetrainingPolicyTimeSeriesOptionsArgs
    Time Series project options used to build new models.
    Trigger DeploymentRetrainingPolicyTriggerArgs
    Retraining policy trigger.
    action String
    The the action to take on the resultant new model.
    autopilotOptions DeploymentRetrainingPolicyAutopilotOptions
    Options for projects used to build new models.
    deploymentId String
    The ID of the Deployment for the Retraining Policy.
    description String
    The description of the Retraining Policy.
    featureListStrategy String
    The feature list strategy used for modeling.
    modelSelectionStrategy String
    Determines how the new model is selected when the retraining policy runs.
    name String
    The name of the Retraining Policy.
    projectOptions DeploymentRetrainingPolicyProjectOptions
    Options for projects used to build new models.
    projectOptionsStrategy String
    The project option strategy used for modeling.
    timeSeriesOptions DeploymentRetrainingPolicyTimeSeriesOptions
    Time Series project options used to build new models.
    trigger DeploymentRetrainingPolicyTrigger
    Retraining policy trigger.
    action string
    The the action to take on the resultant new model.
    autopilotOptions DeploymentRetrainingPolicyAutopilotOptions
    Options for projects used to build new models.
    deploymentId string
    The ID of the Deployment for the Retraining Policy.
    description string
    The description of the Retraining Policy.
    featureListStrategy string
    The feature list strategy used for modeling.
    modelSelectionStrategy string
    Determines how the new model is selected when the retraining policy runs.
    name string
    The name of the Retraining Policy.
    projectOptions DeploymentRetrainingPolicyProjectOptions
    Options for projects used to build new models.
    projectOptionsStrategy string
    The project option strategy used for modeling.
    timeSeriesOptions DeploymentRetrainingPolicyTimeSeriesOptions
    Time Series project options used to build new models.
    trigger DeploymentRetrainingPolicyTrigger
    Retraining policy trigger.
    action str
    The the action to take on the resultant new model.
    autopilot_options DeploymentRetrainingPolicyAutopilotOptionsArgs
    Options for projects used to build new models.
    deployment_id str
    The ID of the Deployment for the Retraining Policy.
    description str
    The description of the Retraining Policy.
    feature_list_strategy str
    The feature list strategy used for modeling.
    model_selection_strategy str
    Determines how the new model is selected when the retraining policy runs.
    name str
    The name of the Retraining Policy.
    project_options DeploymentRetrainingPolicyProjectOptionsArgs
    Options for projects used to build new models.
    project_options_strategy str
    The project option strategy used for modeling.
    time_series_options DeploymentRetrainingPolicyTimeSeriesOptionsArgs
    Time Series project options used to build new models.
    trigger DeploymentRetrainingPolicyTriggerArgs
    Retraining policy trigger.
    action String
    The the action to take on the resultant new model.
    autopilotOptions Property Map
    Options for projects used to build new models.
    deploymentId String
    The ID of the Deployment for the Retraining Policy.
    description String
    The description of the Retraining Policy.
    featureListStrategy String
    The feature list strategy used for modeling.
    modelSelectionStrategy String
    Determines how the new model is selected when the retraining policy runs.
    name String
    The name of the Retraining Policy.
    projectOptions Property Map
    Options for projects used to build new models.
    projectOptionsStrategy String
    The project option strategy used for modeling.
    timeSeriesOptions Property Map
    Time Series project options used to build new models.
    trigger Property Map
    Retraining policy trigger.

    Supporting Types

    DeploymentRetrainingPolicyAutopilotOptions, DeploymentRetrainingPolicyAutopilotOptionsArgs

    BlendBestModels bool
    Blend best models during Autopilot run. This option is not supported in SHAP-only mode.
    Mode string
    The autopiltot mode.
    RunLeakageRemovedFeatureList bool
    Run Autopilot on Leakage Removed feature list (if exists).
    ScoringCodeOnly bool
    Keep only models that can be converted to scorable java code during Autopilot run.
    ShapOnlyMode bool
    Include only models with SHAP value support.
    BlendBestModels bool
    Blend best models during Autopilot run. This option is not supported in SHAP-only mode.
    Mode string
    The autopiltot mode.
    RunLeakageRemovedFeatureList bool
    Run Autopilot on Leakage Removed feature list (if exists).
    ScoringCodeOnly bool
    Keep only models that can be converted to scorable java code during Autopilot run.
    ShapOnlyMode bool
    Include only models with SHAP value support.
    blendBestModels Boolean
    Blend best models during Autopilot run. This option is not supported in SHAP-only mode.
    mode String
    The autopiltot mode.
    runLeakageRemovedFeatureList Boolean
    Run Autopilot on Leakage Removed feature list (if exists).
    scoringCodeOnly Boolean
    Keep only models that can be converted to scorable java code during Autopilot run.
    shapOnlyMode Boolean
    Include only models with SHAP value support.
    blendBestModels boolean
    Blend best models during Autopilot run. This option is not supported in SHAP-only mode.
    mode string
    The autopiltot mode.
    runLeakageRemovedFeatureList boolean
    Run Autopilot on Leakage Removed feature list (if exists).
    scoringCodeOnly boolean
    Keep only models that can be converted to scorable java code during Autopilot run.
    shapOnlyMode boolean
    Include only models with SHAP value support.
    blend_best_models bool
    Blend best models during Autopilot run. This option is not supported in SHAP-only mode.
    mode str
    The autopiltot mode.
    run_leakage_removed_feature_list bool
    Run Autopilot on Leakage Removed feature list (if exists).
    scoring_code_only bool
    Keep only models that can be converted to scorable java code during Autopilot run.
    shap_only_mode bool
    Include only models with SHAP value support.
    blendBestModels Boolean
    Blend best models during Autopilot run. This option is not supported in SHAP-only mode.
    mode String
    The autopiltot mode.
    runLeakageRemovedFeatureList Boolean
    Run Autopilot on Leakage Removed feature list (if exists).
    scoringCodeOnly Boolean
    Keep only models that can be converted to scorable java code during Autopilot run.
    shapOnlyMode Boolean
    Include only models with SHAP value support.

    DeploymentRetrainingPolicyProjectOptions, DeploymentRetrainingPolicyProjectOptionsArgs

    CvMethod string
    The partitioning method for projects used to build new models.
    HoldoutPct double
    The percentage of dataset to assign to holdout set in projects used to build new models.
    Metric string
    The model selection metric in projects used to build new models.
    Reps double
    The number of cross validation folds to use for projects used to build new models.
    ValidationPct double
    The percentage of dataset to assign to validation set in projects used to build new models.
    ValidationType string
    The validation type for projects used to build new models.
    CvMethod string
    The partitioning method for projects used to build new models.
    HoldoutPct float64
    The percentage of dataset to assign to holdout set in projects used to build new models.
    Metric string
    The model selection metric in projects used to build new models.
    Reps float64
    The number of cross validation folds to use for projects used to build new models.
    ValidationPct float64
    The percentage of dataset to assign to validation set in projects used to build new models.
    ValidationType string
    The validation type for projects used to build new models.
    cvMethod String
    The partitioning method for projects used to build new models.
    holdoutPct Double
    The percentage of dataset to assign to holdout set in projects used to build new models.
    metric String
    The model selection metric in projects used to build new models.
    reps Double
    The number of cross validation folds to use for projects used to build new models.
    validationPct Double
    The percentage of dataset to assign to validation set in projects used to build new models.
    validationType String
    The validation type for projects used to build new models.
    cvMethod string
    The partitioning method for projects used to build new models.
    holdoutPct number
    The percentage of dataset to assign to holdout set in projects used to build new models.
    metric string
    The model selection metric in projects used to build new models.
    reps number
    The number of cross validation folds to use for projects used to build new models.
    validationPct number
    The percentage of dataset to assign to validation set in projects used to build new models.
    validationType string
    The validation type for projects used to build new models.
    cv_method str
    The partitioning method for projects used to build new models.
    holdout_pct float
    The percentage of dataset to assign to holdout set in projects used to build new models.
    metric str
    The model selection metric in projects used to build new models.
    reps float
    The number of cross validation folds to use for projects used to build new models.
    validation_pct float
    The percentage of dataset to assign to validation set in projects used to build new models.
    validation_type str
    The validation type for projects used to build new models.
    cvMethod String
    The partitioning method for projects used to build new models.
    holdoutPct Number
    The percentage of dataset to assign to holdout set in projects used to build new models.
    metric String
    The model selection metric in projects used to build new models.
    reps Number
    The number of cross validation folds to use for projects used to build new models.
    validationPct Number
    The percentage of dataset to assign to validation set in projects used to build new models.
    validationType String
    The validation type for projects used to build new models.

    DeploymentRetrainingPolicyTimeSeriesOptions, DeploymentRetrainingPolicyTimeSeriesOptionsArgs

    CalendarId string
    The ID of the calendar to be used in this project.
    DifferencingMethod string
    For time series projects only. Used to specify which differencing method to apply if the data is stationary. For classification problems simple and seasonal are not allowed. Parameter periodicities must be specified if seasonal is chosen. Defaults to auto.
    ExponentiallyWeightedMovingAlpha double
    Discount factor (alpha) used for exponentially weighted moving features.
    Periodicities List<DataRobotDeploymentRetrainingPolicyTimeSeriesOptionsPeriodicity>
    A list of periodicities for time series projects only. For classification problems periodicities are not allowed. If this is provided, parameter 'differencing*method' will default to 'seasonal' if not provided or 'auto'.
    TreatAsExponential string
    For time series projects only. Used to specify whether to treat data as exponential trend and apply transformations like log-transform. For classification problems always is not allowed. Defaults to auto.
    CalendarId string
    The ID of the calendar to be used in this project.
    DifferencingMethod string
    For time series projects only. Used to specify which differencing method to apply if the data is stationary. For classification problems simple and seasonal are not allowed. Parameter periodicities must be specified if seasonal is chosen. Defaults to auto.
    ExponentiallyWeightedMovingAlpha float64
    Discount factor (alpha) used for exponentially weighted moving features.
    Periodicities []DeploymentRetrainingPolicyTimeSeriesOptionsPeriodicity
    A list of periodicities for time series projects only. For classification problems periodicities are not allowed. If this is provided, parameter 'differencing*method' will default to 'seasonal' if not provided or 'auto'.
    TreatAsExponential string
    For time series projects only. Used to specify whether to treat data as exponential trend and apply transformations like log-transform. For classification problems always is not allowed. Defaults to auto.
    calendarId String
    The ID of the calendar to be used in this project.
    differencingMethod String
    For time series projects only. Used to specify which differencing method to apply if the data is stationary. For classification problems simple and seasonal are not allowed. Parameter periodicities must be specified if seasonal is chosen. Defaults to auto.
    exponentiallyWeightedMovingAlpha Double
    Discount factor (alpha) used for exponentially weighted moving features.
    periodicities List<DeploymentRetrainingPolicyTimeSeriesOptionsPeriodicity>
    A list of periodicities for time series projects only. For classification problems periodicities are not allowed. If this is provided, parameter 'differencing*method' will default to 'seasonal' if not provided or 'auto'.
    treatAsExponential String
    For time series projects only. Used to specify whether to treat data as exponential trend and apply transformations like log-transform. For classification problems always is not allowed. Defaults to auto.
    calendarId string
    The ID of the calendar to be used in this project.
    differencingMethod string
    For time series projects only. Used to specify which differencing method to apply if the data is stationary. For classification problems simple and seasonal are not allowed. Parameter periodicities must be specified if seasonal is chosen. Defaults to auto.
    exponentiallyWeightedMovingAlpha number
    Discount factor (alpha) used for exponentially weighted moving features.
    periodicities DeploymentRetrainingPolicyTimeSeriesOptionsPeriodicity[]
    A list of periodicities for time series projects only. For classification problems periodicities are not allowed. If this is provided, parameter 'differencing*method' will default to 'seasonal' if not provided or 'auto'.
    treatAsExponential string
    For time series projects only. Used to specify whether to treat data as exponential trend and apply transformations like log-transform. For classification problems always is not allowed. Defaults to auto.
    calendar_id str
    The ID of the calendar to be used in this project.
    differencing_method str
    For time series projects only. Used to specify which differencing method to apply if the data is stationary. For classification problems simple and seasonal are not allowed. Parameter periodicities must be specified if seasonal is chosen. Defaults to auto.
    exponentially_weighted_moving_alpha float
    Discount factor (alpha) used for exponentially weighted moving features.
    periodicities Sequence[DeploymentRetrainingPolicyTimeSeriesOptionsPeriodicity]
    A list of periodicities for time series projects only. For classification problems periodicities are not allowed. If this is provided, parameter 'differencing*method' will default to 'seasonal' if not provided or 'auto'.
    treat_as_exponential str
    For time series projects only. Used to specify whether to treat data as exponential trend and apply transformations like log-transform. For classification problems always is not allowed. Defaults to auto.
    calendarId String
    The ID of the calendar to be used in this project.
    differencingMethod String
    For time series projects only. Used to specify which differencing method to apply if the data is stationary. For classification problems simple and seasonal are not allowed. Parameter periodicities must be specified if seasonal is chosen. Defaults to auto.
    exponentiallyWeightedMovingAlpha Number
    Discount factor (alpha) used for exponentially weighted moving features.
    periodicities List<Property Map>
    A list of periodicities for time series projects only. For classification problems periodicities are not allowed. If this is provided, parameter 'differencing*method' will default to 'seasonal' if not provided or 'auto'.
    treatAsExponential String
    For time series projects only. Used to specify whether to treat data as exponential trend and apply transformations like log-transform. For classification problems always is not allowed. Defaults to auto.

    DeploymentRetrainingPolicyTimeSeriesOptionsPeriodicity, DeploymentRetrainingPolicyTimeSeriesOptionsPeriodicityArgs

    TimeSteps int
    The number of time steps.
    TimeUnit string
    The time unit or ROW if windowsBasisUnit is ROW
    TimeSteps int
    The number of time steps.
    TimeUnit string
    The time unit or ROW if windowsBasisUnit is ROW
    timeSteps Integer
    The number of time steps.
    timeUnit String
    The time unit or ROW if windowsBasisUnit is ROW
    timeSteps number
    The number of time steps.
    timeUnit string
    The time unit or ROW if windowsBasisUnit is ROW
    time_steps int
    The number of time steps.
    time_unit str
    The time unit or ROW if windowsBasisUnit is ROW
    timeSteps Number
    The number of time steps.
    timeUnit String
    The time unit or ROW if windowsBasisUnit is ROW

    DeploymentRetrainingPolicyTrigger, DeploymentRetrainingPolicyTriggerArgs

    CustomJobId string
    Custom job ID for the retraining policy.
    MinIntervalBetweenRuns string
    Minimal interval between policy runs in ISO 8601 duration string.
    Schedule DataRobotDeploymentRetrainingPolicyTriggerSchedule
    Schedule for the retraining policy.
    StatusDeclinesToFailing bool
    Identifies when trigger type is based on deployment a health status, whether the policy will run when health status declines to failing.
    StatusDeclinesToWarning bool
    Identifies when trigger type is based on deployment a health status, whether the policy will run when health status declines to warning.
    StatusStillInDecline bool
    Identifies when trigger type is based on deployment a health status, whether the policy will run when health status still in decline.
    Type string
    Type of retraining policy trigger.
    CustomJobId string
    Custom job ID for the retraining policy.
    MinIntervalBetweenRuns string
    Minimal interval between policy runs in ISO 8601 duration string.
    Schedule DeploymentRetrainingPolicyTriggerSchedule
    Schedule for the retraining policy.
    StatusDeclinesToFailing bool
    Identifies when trigger type is based on deployment a health status, whether the policy will run when health status declines to failing.
    StatusDeclinesToWarning bool
    Identifies when trigger type is based on deployment a health status, whether the policy will run when health status declines to warning.
    StatusStillInDecline bool
    Identifies when trigger type is based on deployment a health status, whether the policy will run when health status still in decline.
    Type string
    Type of retraining policy trigger.
    customJobId String
    Custom job ID for the retraining policy.
    minIntervalBetweenRuns String
    Minimal interval between policy runs in ISO 8601 duration string.
    schedule DeploymentRetrainingPolicyTriggerSchedule
    Schedule for the retraining policy.
    statusDeclinesToFailing Boolean
    Identifies when trigger type is based on deployment a health status, whether the policy will run when health status declines to failing.
    statusDeclinesToWarning Boolean
    Identifies when trigger type is based on deployment a health status, whether the policy will run when health status declines to warning.
    statusStillInDecline Boolean
    Identifies when trigger type is based on deployment a health status, whether the policy will run when health status still in decline.
    type String
    Type of retraining policy trigger.
    customJobId string
    Custom job ID for the retraining policy.
    minIntervalBetweenRuns string
    Minimal interval between policy runs in ISO 8601 duration string.
    schedule DeploymentRetrainingPolicyTriggerSchedule
    Schedule for the retraining policy.
    statusDeclinesToFailing boolean
    Identifies when trigger type is based on deployment a health status, whether the policy will run when health status declines to failing.
    statusDeclinesToWarning boolean
    Identifies when trigger type is based on deployment a health status, whether the policy will run when health status declines to warning.
    statusStillInDecline boolean
    Identifies when trigger type is based on deployment a health status, whether the policy will run when health status still in decline.
    type string
    Type of retraining policy trigger.
    custom_job_id str
    Custom job ID for the retraining policy.
    min_interval_between_runs str
    Minimal interval between policy runs in ISO 8601 duration string.
    schedule DeploymentRetrainingPolicyTriggerSchedule
    Schedule for the retraining policy.
    status_declines_to_failing bool
    Identifies when trigger type is based on deployment a health status, whether the policy will run when health status declines to failing.
    status_declines_to_warning bool
    Identifies when trigger type is based on deployment a health status, whether the policy will run when health status declines to warning.
    status_still_in_decline bool
    Identifies when trigger type is based on deployment a health status, whether the policy will run when health status still in decline.
    type str
    Type of retraining policy trigger.
    customJobId String
    Custom job ID for the retraining policy.
    minIntervalBetweenRuns String
    Minimal interval between policy runs in ISO 8601 duration string.
    schedule Property Map
    Schedule for the retraining policy.
    statusDeclinesToFailing Boolean
    Identifies when trigger type is based on deployment a health status, whether the policy will run when health status declines to failing.
    statusDeclinesToWarning Boolean
    Identifies when trigger type is based on deployment a health status, whether the policy will run when health status declines to warning.
    statusStillInDecline Boolean
    Identifies when trigger type is based on deployment a health status, whether the policy will run when health status still in decline.
    type String
    Type of retraining policy trigger.

    DeploymentRetrainingPolicyTriggerSchedule, DeploymentRetrainingPolicyTriggerScheduleArgs

    DayOfMonths List<string>
    Days of the month when the job will run.
    DayOfWeeks List<string>
    Days of the week when the job will run.
    Hours List<string>
    Hours of the day when the job will run.
    Minutes List<string>
    Minutes of the day when the job will run.
    Months List<string>
    Months of the year when the job will run.
    DayOfMonths []string
    Days of the month when the job will run.
    DayOfWeeks []string
    Days of the week when the job will run.
    Hours []string
    Hours of the day when the job will run.
    Minutes []string
    Minutes of the day when the job will run.
    Months []string
    Months of the year when the job will run.
    dayOfMonths List<String>
    Days of the month when the job will run.
    dayOfWeeks List<String>
    Days of the week when the job will run.
    hours List<String>
    Hours of the day when the job will run.
    minutes List<String>
    Minutes of the day when the job will run.
    months List<String>
    Months of the year when the job will run.
    dayOfMonths string[]
    Days of the month when the job will run.
    dayOfWeeks string[]
    Days of the week when the job will run.
    hours string[]
    Hours of the day when the job will run.
    minutes string[]
    Minutes of the day when the job will run.
    months string[]
    Months of the year when the job will run.
    day_of_months Sequence[str]
    Days of the month when the job will run.
    day_of_weeks Sequence[str]
    Days of the week when the job will run.
    hours Sequence[str]
    Hours of the day when the job will run.
    minutes Sequence[str]
    Minutes of the day when the job will run.
    months Sequence[str]
    Months of the year when the job will run.
    dayOfMonths List<String>
    Days of the month when the job will run.
    dayOfWeeks List<String>
    Days of the week when the job will run.
    hours List<String>
    Hours of the day when the job will run.
    minutes List<String>
    Minutes of the day when the job will run.
    months List<String>
    Months of the year when the job will run.

    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
    DataRobot v0.8.16 published on Tuesday, Mar 18, 2025 by DataRobot, Inc.
    datarobot-community/pulumi-datarobot