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DataRobot v0.9.0 published on Tuesday, Apr 8, 2025 by DataRobot, Inc.
datarobot-community/pulumi-datarobot

datarobot.DeploymentRetrainingPolicy

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DataRobot v0.9.0 published on Tuesday, Apr 8, 2025 by DataRobot, Inc.
datarobot-community/pulumi-datarobot

Deployment Retraining Policy

Example Usage

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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());
    }
}
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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}
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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 This property is required. string
The unique name of the resource.
args This property is required. DeploymentRetrainingPolicyArgs
The arguments to resource properties.
opts CustomResourceOptions
Bag of options to control resource's behavior.
resource_name This property is required. str
The unique name of the resource.
args This property is required. 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 This property is required. string
The unique name of the resource.
args This property is required. DeploymentRetrainingPolicyArgs
The arguments to resource properties.
opts ResourceOption
Bag of options to control resource's behavior.
name This property is required. string
The unique name of the resource.
args This property is required. DeploymentRetrainingPolicyArgs
The arguments to resource properties.
opts CustomResourceOptions
Bag of options to control resource's behavior.
name This property is required. String
The unique name of the resource.
args This property is required. 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",
    },
});
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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"),
	},
})
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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());
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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",
    })
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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",
    },
});
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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
Copy

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 This property is required. string
The ID of the Deployment for the Retraining Policy.
Description This property is required. 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 This property is required. string
The ID of the Deployment for the Retraining Policy.
Description This property is required. 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 This property is required. String
The ID of the Deployment for the Retraining Policy.
description This property is required. 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 This property is required. string
The ID of the Deployment for the Retraining Policy.
description This property is required. 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 This property is required. str
The ID of the Deployment for the Retraining Policy.
description This property is required. 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 This property is required. String
The ID of the Deployment for the Retraining Policy.
description This property is required. 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 This property is required.
The unique name of the resulting resource.
id This property is required.
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 This property is required.
The unique name of the resulting resource.
id This property is required.
The unique provider ID of the resource to lookup.
name This property is required.
The unique name of the resulting resource.
id This property is required.
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 This property is required.
The unique name of the resulting resource.
id This property is required.
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 This property is required.
The unique name of the resulting resource.
id This property is required.
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 This property is required. int
The number of time steps.
TimeUnit This property is required. string
The time unit or ROW if windowsBasisUnit is ROW
TimeSteps This property is required. int
The number of time steps.
TimeUnit This property is required. string
The time unit or ROW if windowsBasisUnit is ROW
timeSteps This property is required. Integer
The number of time steps.
timeUnit This property is required. String
The time unit or ROW if windowsBasisUnit is ROW
timeSteps This property is required. number
The number of time steps.
timeUnit This property is required. string
The time unit or ROW if windowsBasisUnit is ROW
time_steps This property is required. int
The number of time steps.
time_unit This property is required. str
The time unit or ROW if windowsBasisUnit is ROW
timeSteps This property is required. Number
The number of time steps.
timeUnit This property is required. 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 This property is required. List<string>
Days of the month when the job will run.
DayOfWeeks This property is required. List<string>
Days of the week when the job will run.
Hours This property is required. List<string>
Hours of the day when the job will run.
Minutes This property is required. List<string>
Minutes of the day when the job will run.
Months This property is required. List<string>
Months of the year when the job will run.
DayOfMonths This property is required. []string
Days of the month when the job will run.
DayOfWeeks This property is required. []string
Days of the week when the job will run.
Hours This property is required. []string
Hours of the day when the job will run.
Minutes This property is required. []string
Minutes of the day when the job will run.
Months This property is required. []string
Months of the year when the job will run.
dayOfMonths This property is required. List<String>
Days of the month when the job will run.
dayOfWeeks This property is required. List<String>
Days of the week when the job will run.
hours This property is required. List<String>
Hours of the day when the job will run.
minutes This property is required. List<String>
Minutes of the day when the job will run.
months This property is required. List<String>
Months of the year when the job will run.
dayOfMonths This property is required. string[]
Days of the month when the job will run.
dayOfWeeks This property is required. string[]
Days of the week when the job will run.
hours This property is required. string[]
Hours of the day when the job will run.
minutes This property is required. string[]
Minutes of the day when the job will run.
months This property is required. string[]
Months of the year when the job will run.
day_of_months This property is required. Sequence[str]
Days of the month when the job will run.
day_of_weeks This property is required. Sequence[str]
Days of the week when the job will run.
hours This property is required. Sequence[str]
Hours of the day when the job will run.
minutes This property is required. Sequence[str]
Minutes of the day when the job will run.
months This property is required. Sequence[str]
Months of the year when the job will run.
dayOfMonths This property is required. List<String>
Days of the month when the job will run.
dayOfWeeks This property is required. List<String>
Days of the week when the job will run.
hours This property is required. List<String>
Hours of the day when the job will run.
minutes This property is required. List<String>
Minutes of the day when the job will run.
months This property is required. 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 v0.9.0 published on Tuesday, Apr 8, 2025 by DataRobot, Inc.
datarobot-community/pulumi-datarobot