@pulumiverse/grafana
Version:
A Pulumi package for creating and managing grafana.
256 lines • 9.2 kB
JavaScript
;
// *** WARNING: this file was generated by pulumi-language-nodejs. ***
// *** Do not edit by hand unless you're certain you know what you are doing! ***
Object.defineProperty(exports, "__esModule", { value: true });
exports.Job = void 0;
const pulumi = require("@pulumi/pulumi");
const utilities = require("../utilities");
/**
* A job defines the queries and model parameters for a machine learning task.
*
* See [the Grafana Cloud docs](https://grafana.com/docs/grafana-cloud/alerting-and-irm/machine-learning/dynamic-alerting/forecasting/config/) for more information
* on available hyperparameters for use in the `hyperParams` field.
*
* ## Example Usage
*
* ### Basic Forecast
*
* This forecast uses a Prometheus datasource, where the source query is defined in the `expr` field of the `queryParams` attribute.
*
* Other datasources are supported, but the structure `queryParams` may differ.
*
* ```typescript
* import * as pulumi from "@pulumi/pulumi";
* import * as grafana from "@pulumiverse/grafana";
*
* const foo = new grafana.oss.DataSource("foo", {
* type: "prometheus",
* name: "prometheus-ds-test",
* uid: "prometheus-ds-test-uid",
* url: "https://my-instance.com",
* basicAuthEnabled: true,
* basicAuthUsername: "username",
* jsonDataEncoded: JSON.stringify({
* httpMethod: "POST",
* prometheusType: "Mimir",
* prometheusVersion: "2.4.0",
* }),
* secureJsonDataEncoded: JSON.stringify({
* basicAuthPassword: "password",
* }),
* });
* const testJob = new grafana.machinelearning.Job("test_job", {
* name: "Test Job",
* metric: "tf_test_job",
* datasourceType: "prometheus",
* datasourceUid: foo.uid,
* queryParams: {
* expr: "grafanacloud_grafana_instance_active_user_count",
* },
* });
* ```
*
* ### Tuned Forecast
*
* This forecast has tuned hyperparameters to improve the accuracy of the model.
*
* ```typescript
* import * as pulumi from "@pulumi/pulumi";
* import * as grafana from "@pulumiverse/grafana";
*
* const foo = new grafana.oss.DataSource("foo", {
* type: "prometheus",
* name: "prometheus-ds-test",
* uid: "prometheus-ds-test-uid",
* url: "https://my-instance.com",
* basicAuthEnabled: true,
* basicAuthUsername: "username",
* jsonDataEncoded: JSON.stringify({
* httpMethod: "POST",
* prometheusType: "Mimir",
* prometheusVersion: "2.4.0",
* }),
* secureJsonDataEncoded: JSON.stringify({
* basicAuthPassword: "password",
* }),
* });
* const testJob = new grafana.machinelearning.Job("test_job", {
* name: "Test Job",
* metric: "tf_test_job",
* datasourceType: "prometheus",
* datasourceUid: foo.uid,
* queryParams: {
* expr: "grafanacloud_grafana_instance_active_user_count",
* },
* hyperParams: {
* daily_seasonality: "15",
* weekly_seasonality: "10",
* },
* customLabels: {
* example_label: "example_value",
* },
* });
* ```
*
* ### Rescaled Forecast
*
* This forecast has had the data transformed using a power transformation in order to avoid negative lower predictions.
*
* ```typescript
* import * as pulumi from "@pulumi/pulumi";
* import * as grafana from "@pulumiverse/grafana";
*
* const foo = new grafana.oss.DataSource("foo", {
* type: "prometheus",
* name: "prometheus-ds-test",
* uid: "prometheus-ds-test-uid",
* url: "https://my-instance.com",
* basicAuthEnabled: true,
* basicAuthUsername: "username",
* jsonDataEncoded: JSON.stringify({
* httpMethod: "POST",
* prometheusType: "Mimir",
* prometheusVersion: "2.4.0",
* }),
* secureJsonDataEncoded: JSON.stringify({
* basicAuthPassword: "password",
* }),
* });
* const testJob = new grafana.machinelearning.Job("test_job", {
* name: "Test Job",
* metric: "tf_test_job",
* datasourceType: "prometheus",
* datasourceUid: foo.uid,
* queryParams: {
* expr: "grafanacloud_grafana_instance_active_user_count",
* },
* hyperParams: {
* transformation_id: "power",
* },
* });
* ```
*
* ### Forecast with Holidays
*
* This forecast has holidays which will be taken into account when training the model.
*
* ```typescript
* import * as pulumi from "@pulumi/pulumi";
* import * as grafana from "@pulumiverse/grafana";
*
* const foo = new grafana.oss.DataSource("foo", {
* type: "prometheus",
* name: "prometheus-ds-test",
* uid: "prometheus-ds-test-uid",
* url: "https://my-instance.com",
* basicAuthEnabled: true,
* basicAuthUsername: "username",
* jsonDataEncoded: JSON.stringify({
* httpMethod: "POST",
* prometheusType: "Mimir",
* prometheusVersion: "2.4.0",
* }),
* secureJsonDataEncoded: JSON.stringify({
* basicAuthPassword: "password",
* }),
* });
* const testHoliday = new grafana.machinelearning.Holiday("test_holiday", {
* name: "Test Holiday",
* customPeriods: [{
* name: "First of January",
* startTime: "2023-01-01T00:00:00Z",
* endTime: "2023-01-02T00:00:00Z",
* }],
* });
* const testJob = new grafana.machinelearning.Job("test_job", {
* name: "Test Job",
* metric: "tf_test_job",
* datasourceType: "prometheus",
* datasourceUid: foo.uid,
* queryParams: {
* expr: "grafanacloud_grafana_instance_active_user_count",
* },
* holidays: [testHoliday.id],
* });
* ```
*
* ## Import
*
* ```sh
* terraform import grafana_machine_learning_job.name "{{ id }}"
* ```
*/
class Job extends pulumi.CustomResource {
/**
* Get an existing Job 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, id, state, opts) {
return new Job(name, state, { ...opts, id: id });
}
/**
* Returns true if the given object is an instance of Job. This is designed to work even
* when multiple copies of the Pulumi SDK have been loaded into the same process.
*/
static isInstance(obj) {
if (obj === undefined || obj === null) {
return false;
}
return obj['__pulumiType'] === Job.__pulumiType;
}
constructor(name, argsOrState, opts) {
let resourceInputs = {};
opts = opts || {};
if (opts.id) {
const state = argsOrState;
resourceInputs["customLabels"] = state?.customLabels;
resourceInputs["datasourceType"] = state?.datasourceType;
resourceInputs["datasourceUid"] = state?.datasourceUid;
resourceInputs["description"] = state?.description;
resourceInputs["holidays"] = state?.holidays;
resourceInputs["hyperParams"] = state?.hyperParams;
resourceInputs["interval"] = state?.interval;
resourceInputs["metric"] = state?.metric;
resourceInputs["name"] = state?.name;
resourceInputs["queryParams"] = state?.queryParams;
resourceInputs["trainingWindow"] = state?.trainingWindow;
}
else {
const args = argsOrState;
if (args?.datasourceType === undefined && !opts.urn) {
throw new Error("Missing required property 'datasourceType'");
}
if (args?.datasourceUid === undefined && !opts.urn) {
throw new Error("Missing required property 'datasourceUid'");
}
if (args?.metric === undefined && !opts.urn) {
throw new Error("Missing required property 'metric'");
}
if (args?.queryParams === undefined && !opts.urn) {
throw new Error("Missing required property 'queryParams'");
}
resourceInputs["customLabels"] = args?.customLabels;
resourceInputs["datasourceType"] = args?.datasourceType;
resourceInputs["datasourceUid"] = args?.datasourceUid;
resourceInputs["description"] = args?.description;
resourceInputs["holidays"] = args?.holidays;
resourceInputs["hyperParams"] = args?.hyperParams;
resourceInputs["interval"] = args?.interval;
resourceInputs["metric"] = args?.metric;
resourceInputs["name"] = args?.name;
resourceInputs["queryParams"] = args?.queryParams;
resourceInputs["trainingWindow"] = args?.trainingWindow;
}
opts = pulumi.mergeOptions(utilities.resourceOptsDefaults(), opts);
super(Job.__pulumiType, name, resourceInputs, opts);
}
}
exports.Job = Job;
/** @internal */
Job.__pulumiType = 'grafana:machineLearning/job:Job';
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