@pulumi/databricks/mlflowModel.d.ts

A Pulumi package for creating and managing databricks cloud resources.

import * as pulumi from "@pulumi/pulumi";
import * as inputs from "./types/input";
import * as outputs from "./types/output";
/**
 * This resource allows you to create [MLflow models](https://docs.databricks.com/applications/mlflow/models.html) in Databricks.
 *
 * > This resource can only be used with a workspace-level provider!
 *
 * > This documentation covers the Workspace Model Registry. Databricks recommends using Models in Unity Catalog. Models in Unity Catalog provides centralized model governance, cross-workspace access, lineage, and deployment.
 *
 * ## Example Usage
 *
 * ```typescript
 * import * as pulumi from "@pulumi/pulumi";
 * import * as databricks from "@pulumi/databricks";
 *
 * const test = new databricks.MlflowModel("test", {
 *     name: "My MLflow Model",
 *     description: "My MLflow model description",
 *     tags: [
 *         {
 *             key: "key1",
 *             value: "value1",
 *         },
 *         {
 *             key: "key2",
 *             value: "value2",
 *         },
 *     ],
 * });
 * ```
 *
 * ## Access Control
 *
 * * databricks.Permissions can control which groups or individual users can *Read*, *Edit*, *Manage Staging Versions*, *Manage Production Versions*, and *Manage* individual models.
 *
 * ## Related Resources
 *
 * The following resources are often used in the same context:
 *
 * * databricks.RegisteredModel to create [Models in Unity Catalog](https://docs.databricks.com/en/mlflow/models-in-uc.html) in Databricks.
 * * End to end workspace management guide.
 * * databricks.ModelServing to serve this model on a Databricks serving endpoint.
 * * databricks.Directory to manage directories in [Databricks Workspace](https://docs.databricks.com/workspace/workspace-objects.html).
 * * databricks.MlflowExperiment to manage [MLflow experiments](https://docs.databricks.com/data/data-sources/mlflow-experiment.html) in Databricks.
 * * databricks.Notebook to manage [Databricks Notebooks](https://docs.databricks.com/notebooks/index.html).
 * * databricks.Notebook data to export a notebook from Databricks Workspace.
 * * databricks.Repo to manage [Databricks Repos](https://docs.databricks.com/repos.html).
 *
 * ## Import
 *
 * The model resource can be imported using the name
 *
 * hcl
 *
 * import {
 *
 *   to = databricks_mlflow_model.this
 *
 *   id = "<name>"
 *
 * }
 *
 * Alternatively, when using `terraform` version 1.4 or earlier, import using the `pulumi import` command:
 *
 * bash
 *
 * ```sh
 * $ pulumi import databricks:index/mlflowModel:MlflowModel this <name>
 * ```
 */
export declare class MlflowModel extends pulumi.CustomResource {
    /**
     * Get an existing MlflowModel resource's state with the given name, ID, and optional extra
     * properties used to qualify the lookup.
     *
     * @param name The _unique_ name of the resulting resource.
     * @param id The _unique_ provider ID of the resource to lookup.
     * @param state Any extra arguments used during the lookup.
     * @param opts Optional settings to control the behavior of the CustomResource.
     */
    static get(name: string, id: pulumi.Input<pulumi.ID>, state?: MlflowModelState, opts?: pulumi.CustomResourceOptions): MlflowModel;
    /**
     * Returns true if the given object is an instance of MlflowModel.  This is designed to work even
     * when multiple copies of the Pulumi SDK have been loaded into the same process.
     */
    static isInstance(obj: any): obj is MlflowModel;
    /**
     * The description of the MLflow model.
     */
    readonly description: pulumi.Output<string | undefined>;
    /**
     * Name of MLflow model. Change of name triggers new resource.
     */
    readonly name: pulumi.Output<string>;
    readonly registeredModelId: pulumi.Output<string>;
    /**
     * Tags for the MLflow model.
     */
    readonly tags: pulumi.Output<outputs.MlflowModelTag[] | undefined>;
    /**
     * Create a MlflowModel resource with the given unique name, arguments, and options.
     *
     * @param name The _unique_ name of the resource.
     * @param args The arguments to use to populate this resource's properties.
     * @param opts A bag of options that control this resource's behavior.
     */
    constructor(name: string, args?: MlflowModelArgs, opts?: pulumi.CustomResourceOptions);
}
/**
 * Input properties used for looking up and filtering MlflowModel resources.
 */
export interface MlflowModelState {
    /**
     * The description of the MLflow model.
     */
    description?: pulumi.Input<string>;
    /**
     * Name of MLflow model. Change of name triggers new resource.
     */
    name?: pulumi.Input<string>;
    registeredModelId?: pulumi.Input<string>;
    /**
     * Tags for the MLflow model.
     */
    tags?: pulumi.Input<pulumi.Input<inputs.MlflowModelTag>[]>;
}
/**
 * The set of arguments for constructing a MlflowModel resource.
 */
export interface MlflowModelArgs {
    /**
     * The description of the MLflow model.
     */
    description?: pulumi.Input<string>;
    /**
     * Name of MLflow model. Change of name triggers new resource.
     */
    name?: pulumi.Input<string>;
    /**
     * Tags for the MLflow model.
     */
    tags?: pulumi.Input<pulumi.Input<inputs.MlflowModelTag>[]>;
}