Allow Machine Learning jobs to be specified using datasource UID (#707)

The Grafana Machine Learning API now supports jobs to specify their datasource
using UID; this PR updates the Terraform provider to also allow this.

Author: sd2k

docs/resources/machine_learning_job.md

@@ -17,14 +17,15 @@ A job defines the queries and model parameters for a machine learning task.
 
 ### Required
 
-- `datasource_id` (Number) The id of the datasource to query.
 - `datasource_type` (String) The type of datasource being queried. Currently allowed values are prometheus, graphite, loki, postgres, and datadog.
 - `metric` (String) The metric used to query the job results.
 - `name` (String) The name of the job.
 - `query_params` (Map of String) An object representing the query params to query Grafana with.
 
 ### Optional
 
+- `datasource_id` (Number) The id of the datasource to query.
+- `datasource_uid` (String) The uid of the datasource to query.
 - `description` (String) A description of the job.
 - `hyper_params` (Map of String) The hyperparameters used to fine tune the algorithm. See https://grafana.com/docs/grafana-cloud/machine-learning/models/ for the full list of available hyperparameters. Defaults to `map[]`.
 - `interval` (Number) The data interval in seconds to train the data on. Defaults to `300`.

examples/resources/grafana_machine_learning_job/datasource_uid_job.tf

@@ -0,0 +1,9 @@
+resource "grafana_machine_learning_job" "test_job" {
+  name            = "Test Job"
+  metric          = "tf_test_job"
+  datasource_type = "prometheus"
+  datasource_uid  = "grafanacloud-usage"
+  query_params = {
+    expr = "grafanacloud_grafana_instance_active_user_count"
+  }
+}

examples/resources/grafana_machine_learning_job/tuned_job.tf

@@ -2,7 +2,7 @@ resource "grafana_machine_learning_job" "test_job" {
   name            = "Test Job"
   metric          = "tf_test_job"
   datasource_type = "prometheus"
-  datasource_id   = 10
+  datasource_uid  = "grafanacloud-usage"
   query_params = {
     expr = "grafanacloud_grafana_instance_active_user_count"
   }

go.mod

@@ -6,7 +6,7 @@ require (
 	github.com/Masterminds/semver/v3 v3.1.1
 	github.com/grafana/amixr-api-go-client v0.0.5
 	github.com/grafana/grafana-api-golang-client v0.13.0
-	github.com/grafana/machine-learning-go-client v0.1.1
+	github.com/grafana/machine-learning-go-client v0.2.0
 	github.com/grafana/synthetic-monitoring-agent v0.9.4
 	github.com/grafana/synthetic-monitoring-api-go-client v0.6.3
 	github.com/hashicorp/go-cleanhttp v0.5.2

go.sum

@@ -117,8 +117,8 @@ github.com/grafana/amixr-api-go-client v0.0.5 h1:jqmljnd5FozuOsCNuyhZVpooxmj0BW9
 github.com/grafana/amixr-api-go-client v0.0.5/go.mod h1:N6x26XUrM5zGtK5zL5vNJnAn2JFMxLFPPLTw/6pDkFE=
 github.com/grafana/grafana-api-golang-client v0.13.0 h1:o/gL3F7EjBSBKgrpjH9/+sYFJ0HBUofvAYlKhrT2opE=
 github.com/grafana/grafana-api-golang-client v0.13.0/go.mod h1:24W29gPe9yl0/3A9X624TPkAOR8DpHno490cPwnkv8E=
-github.com/grafana/machine-learning-go-client v0.1.1 h1:Gw6cX8xAd6IVF2LApkXOIdBK8Gzz07B3jQPukecw7fc=
-github.com/grafana/machine-learning-go-client v0.1.1/go.mod h1:QFfZz8NkqVF8++skjkKQXJEZfpCYd8S0yTWJUpsLLTA=
+github.com/grafana/machine-learning-go-client v0.2.0 h1:5JgfJn5Q72D0jZlXnM0gZ9lV4Q4zzq9X0GVfPu8Vxis=
+github.com/grafana/machine-learning-go-client v0.2.0/go.mod h1:QFfZz8NkqVF8++skjkKQXJEZfpCYd8S0yTWJUpsLLTA=
 github.com/grafana/synthetic-monitoring-agent v0.9.4 h1:Enx5s6gFbc/RAzL5KDX/00catAlbcY7/1IFPBe5lo/c=
 github.com/grafana/synthetic-monitoring-agent v0.9.4/go.mod h1:PGcL9plaDkqkWenFE53vCfLamfws3yFba4jgWEt9kGw=
 github.com/grafana/synthetic-monitoring-api-go-client v0.6.3 h1:3jb4v5W8cEEr5zp5kVAzyV0UGF7mm06iY3nBpN4ZCDU=

grafana/resource_machine_learning_job.go

@@ -2,6 +2,7 @@ package grafana
 
 import (
 	"context"
+	"fmt"
 	"time"
 
 	"github.com/hashicorp/terraform-plugin-sdk/v2/diag"
@@ -49,7 +50,12 @@ A job defines the queries and model parameters for a machine learning task.
 			"datasource_id": {
 				Description: "The id of the datasource to query.",
 				Type:        schema.TypeInt,
-				Required:    true,
+				Optional:    true,
+			},
+			"datasource_uid": {
+				Description: "The uid of the datasource to query.",
+				Type:        schema.TypeString,
+				Optional:    true,
 			},
 			"datasource_type": {
 				Description: "The type of datasource being queried. Currently allowed values are prometheus, graphite, loki, postgres, and datadog.",
@@ -85,8 +91,11 @@ A job defines the queries and model parameters for a machine learning task.
 
 func resourceMachineLearningJobCreate(ctx context.Context, d *schema.ResourceData, meta interface{}) diag.Diagnostics {
 	c := meta.(*client).mlapi
-	job := makeMLJob(d, meta)
-	job, err := c.NewJob(ctx, job)
+	job, err := makeMLJob(d, meta)
+	if err != nil {
+		return diag.FromErr(err)
+	}
+	job, err = c.NewJob(ctx, job)
 	if err != nil {
 		return diag.FromErr(err)
 	}
@@ -104,7 +113,16 @@ func resourceMachineLearningJobRead(ctx context.Context, d *schema.ResourceData,
 	d.Set("name", job.Name)
 	d.Set("metric", job.Metric)
 	d.Set("description", job.Description)
-	d.Set("datasource_id", job.DatasourceID)
+	if job.DatasourceID != 0 {
+		d.Set("datasource_id", job.DatasourceID)
+	} else {
+		d.Set("datasource_id", nil)
+	}
+	if job.DatasourceUID != "" {
+		d.Set("datasource_uid", job.DatasourceUID)
+	} else {
+		d.Set("datasource_uid", nil)
+	}
 	d.Set("datasource_type", job.DatasourceType)
 	d.Set("query_params", job.QueryParams)
 	d.Set("interval", job.Interval)
@@ -116,8 +134,11 @@ func resourceMachineLearningJobRead(ctx context.Context, d *schema.ResourceData,
 
 func resourceMachineLearningJobUpdate(ctx context.Context, d *schema.ResourceData, meta interface{}) diag.Diagnostics {
 	c := meta.(*client).mlapi
-	j := makeMLJob(d, meta)
-	_, err := c.UpdateJob(ctx, j)
+	job, err := makeMLJob(d, meta)
+	if err != nil {
+		return diag.FromErr(err)
+	}
+	_, err = c.UpdateJob(ctx, job)
 	if err != nil {
 		return diag.FromErr(err)
 	}
@@ -134,20 +155,26 @@ func resourceMachineLearningJobDelete(ctx context.Context, d *schema.ResourceDat
 	return nil
 }
 
-func makeMLJob(d *schema.ResourceData, meta interface{}) mlapi.Job {
+func makeMLJob(d *schema.ResourceData, meta interface{}) (mlapi.Job, error) {
+	datasourceID := uint(d.Get("datasource_id").(int))
+	datasourceUID := d.Get("datasource_uid").(string)
+	if datasourceID == 0 && datasourceUID == "" {
+		return mlapi.Job{}, fmt.Errorf("either datasource_id or datasource_uid must be set")
+	}
 	return mlapi.Job{
 		ID:                d.Id(),
 		Name:              d.Get("name").(string),
 		Metric:            d.Get("metric").(string),
 		Description:       d.Get("description").(string),
 		GrafanaURL:        meta.(*client).gapiURL,
-		DatasourceID:      uint(d.Get("datasource_id").(int)),
+		DatasourceID:      datasourceID,
+		DatasourceUID:     datasourceUID,
 		DatasourceType:    d.Get("datasource_type").(string),
 		QueryParams:       d.Get("query_params").(map[string]interface{}),
 		Interval:          uint(d.Get("interval").(int)),
 		Algorithm:         "Prophet",
 		HyperParams:       d.Get("hyper_params").(map[string]interface{}),
 		TrainingWindow:    uint(d.Get("training_window").(int)),
 		TrainingFrequency: uint(24 * time.Hour / time.Second),
-	}
+	}, nil
 }

grafana/resource_machine_learning_job_test.go

@@ -33,14 +33,27 @@ func TestAccResourceMachineLearningJob(t *testing.T) {
 					resource.TestCheckResourceAttr("grafana_machine_learning_job.test_job", "training_window", "7776000"),
 				),
 			},
+			{
+				Config: testAccExample(t, "resources/grafana_machine_learning_job/datasource_uid_job.tf"),
+				Check: resource.ComposeTestCheckFunc(
+					resource.TestCheckResourceAttrSet("grafana_machine_learning_job.test_job", "id"),
+					resource.TestCheckResourceAttr("grafana_machine_learning_job.test_job", "name", "Test Job"),
+					resource.TestCheckResourceAttr("grafana_machine_learning_job.test_job", "metric", "tf_test_job"),
+					resource.TestCheckResourceAttr("grafana_machine_learning_job.test_job", "datasource_type", "prometheus"),
+					resource.TestCheckResourceAttr("grafana_machine_learning_job.test_job", "datasource_uid", "grafanacloud-usage"),
+					resource.TestCheckResourceAttr("grafana_machine_learning_job.test_job", "query_params.expr", "grafanacloud_grafana_instance_active_user_count"),
+					resource.TestCheckResourceAttr("grafana_machine_learning_job.test_job", "interval", "300"),
+					resource.TestCheckResourceAttr("grafana_machine_learning_job.test_job", "training_window", "7776000"),
+				),
+			},
 			{
 				Config: testAccExample(t, "resources/grafana_machine_learning_job/tuned_job.tf"),
 				Check: resource.ComposeTestCheckFunc(
 					resource.TestCheckResourceAttrSet("grafana_machine_learning_job.test_job", "id"),
 					resource.TestCheckResourceAttr("grafana_machine_learning_job.test_job", "name", "Test Job"),
 					resource.TestCheckResourceAttr("grafana_machine_learning_job.test_job", "metric", "tf_test_job"),
 					resource.TestCheckResourceAttr("grafana_machine_learning_job.test_job", "datasource_type", "prometheus"),
-					resource.TestCheckResourceAttr("grafana_machine_learning_job.test_job", "datasource_id", "10"),
+					resource.TestCheckResourceAttr("grafana_machine_learning_job.test_job", "datasource_uid", "grafanacloud-usage"),
 					resource.TestCheckResourceAttr("grafana_machine_learning_job.test_job", "query_params.expr", "grafanacloud_grafana_instance_active_user_count"),
 					resource.TestCheckResourceAttr("grafana_machine_learning_job.test_job", "interval", "300"),
 					resource.TestCheckResourceAttr("grafana_machine_learning_job.test_job", "training_window", "7776000"),
@@ -103,6 +116,17 @@ resource "grafana_machine_learning_job" "invalid" {
 }
 `
 
+const machineLearningJobMissingDatasourceIDOrUID = `
+resource "grafana_machine_learning_job" "invalid" {
+  name            = "Test Job"
+  metric          = "tf_test_job"
+  datasource_type = "prometheus"
+  query_params = {
+    expr = "grafanacloud_grafana_instance_active_user_count"
+  }
+}
+`
+
 func TestAccResourceInvalidMachineLearningJob(t *testing.T) {
 	CheckCloudInstanceTestsEnabled(t)
 
@@ -113,6 +137,10 @@ func TestAccResourceInvalidMachineLearningJob(t *testing.T) {
 				Config:      machineLearningJobInvalid,
 				ExpectError: regexp.MustCompile(".*datasourceType.*"),
 			},
+			{
+				Config:      machineLearningJobMissingDatasourceIDOrUID,
+				ExpectError: regexp.MustCompile(".*datasource_id or datasource_uid.*"),
+			},
 		},
 	})
 }