Add resources for creating ML managed alerts

docs/resources/machine_learning_alert.md

@@ -0,0 +1,44 @@
+---
+# generated by https://github.com/hashicorp/terraform-plugin-docs
+page_title: "grafana_machine_learning_alert Resource - terraform-provider-grafana"
+subcategory: "Machine Learning"
+description: |-
+  A job defines the queries and model parameters for a machine learning task.
+---
+
+# grafana_machine_learning_alert (Resource)
+
+A job defines the queries and model parameters for a machine learning task.
+
+
+
+<!-- schema generated by tfplugindocs -->
+## Schema
+
+### Required
+
+- `title` (String) The title of the alert.
+
+### Optional
+
+- `annotations` (Map of String) Annotations to add to the alert generated in Grafana.
+- `anomaly_condition` (String) The condition for when to consider a point as anomalous.
+- `for` (String) How long values must be anomalous before firing an alert.
+- `job` (String) The forecast this alert belongs to.
+- `labels` (Map of String) Labels to add to the alert generated in Grafana.
+- `no_data_state` (String) How the alert should be processed when no data is returned by the underlying series
+- `outlier` (String) The forecast this alert belongs to.
+- `threshold` (String) The threshold of points over the window that need to be anomalous to alert.
+- `window` (String) How much time to average values over
+
+### Read-Only
+
+- `id` (String) The ID of the alert.
+
+## Import
+
+Import is supported using the following syntax:
+
+```shell
+terraform import grafana_machine_learning_alert.name "{{ id }}"
+```

examples/resources/grafana_machine_learning_alert/import.sh

@@ -0,0 +1 @@
+terraform import grafana_machine_learning_alert.name "{{ id }}"

examples/resources/grafana_machine_learning_alert/job_alert.tf

@@ -0,0 +1,36 @@
+resource "grafana_data_source" "foo" {
+  type                = "prometheus"
+  name                = "prometheus-ds-test"
+  uid                 = "prometheus-ds-test-uid"
+  url                 = "https://my-instance.com"
+  basic_auth_enabled  = true
+  basic_auth_username = "username"
+
+  json_data_encoded = jsonencode({
+    httpMethod        = "POST"
+    prometheusType    = "Mimir"
+    prometheusVersion = "2.4.0"
+  })
+
+  secure_json_data_encoded = jsonencode({
+    basicAuthPassword = "password"
+  })
+}
+
+resource "grafana_machine_learning_job" "test_job" {
+  name            = "Test Job"
+  metric          = "tf_test_job"
+  datasource_type = "prometheus"
+  datasource_uid  = grafana_data_source.foo.uid
+  query_params = {
+    expr = "grafanacloud_grafana_instance_active_user_count"
+  }
+}
+
+resource "grafana_machine_learning_alert" "test_job_alert" {
+  job               = grafana_machine_learning_job.test_job
+  title             = "Test Job Alert"
+  anomaly_condition = "any"
+  threshould        = ">0.8"
+  window            = "15m"
+}

examples/resources/grafana_machine_learning_alert/outlier_alert.tf

@@ -0,0 +1,26 @@
+resource "grafana_machine_learning_outlier_detector" "my_dbscan_outlier_detector" {
+  name        = "My DBSCAN outlier detector"
+  description = "My DBSCAN Outlier Detector"
+
+  metric          = "tf_test_dbscan_job"
+  datasource_type = "prometheus"
+  datasource_uid  = "AbCd12345"
+  query_params = {
+    expr = "grafanacloud_grafana_instance_active_user_count"
+  }
+  interval = 300
+
+  algorithm {
+    name        = "dbscan"
+    sensitivity = 0.5
+    config {
+      epsilon = 1.0
+    }
+  }
+}
+
+resource "grafana_machine_learning_alert" "test_job_alert" {
+  job    = grafana_machine_learning_outlier_detector.my_dbscan_outlier_detector
+  title  = "Test Outlier Alert"
+  window = "1h"
+}

go.mod

@@ -12,7 +12,7 @@ require (
 	github.com/grafana/amixr-api-go-client v0.0.12 // main branch
 	github.com/grafana/grafana-com-public-clients/go/gcom v0.0.0-20240322153219-42c6a1d2bcab
 	github.com/grafana/grafana-openapi-client-go v0.0.0-20240523010106-657d101fcbd9
-	github.com/grafana/machine-learning-go-client v0.7.0
+	github.com/grafana/machine-learning-go-client v0.7.1-0.20240703190259-47c2986b5066
 	github.com/grafana/slo-openapi-client/go v0.0.0-20240626093634-e6741482b090
 	github.com/grafana/synthetic-monitoring-agent v0.24.3
 	github.com/grafana/synthetic-monitoring-api-go-client v0.8.0

go.sum

@@ -146,6 +146,10 @@ github.com/grafana/grafana-plugin-sdk-go v0.235.0 h1:UnZ/iBDvCkfDgwR94opi8trAWJX
 github.com/grafana/grafana-plugin-sdk-go v0.235.0/go.mod h1:6n9LbrjGL3xAATntYVNcIi90G9BVHRJjzHKz5FXVfWw=
 github.com/grafana/machine-learning-go-client v0.7.0 h1:yiRBg8rCNbHh9BURa+vtZ8ItRYvabbdYAtsAOfxoFPI=
 github.com/grafana/machine-learning-go-client v0.7.0/go.mod h1:bKsLSJTreH7HXaL2FJnnrliMuP0L8XwMkXte6AgwFFg=
+github.com/grafana/machine-learning-go-client v0.7.1-0.20240702191547-8b1f45f0374c h1:ebjonuo+s2BXsD/pq3slOZc4N8ZXf2Urfvj6dOFu+vg=
+github.com/grafana/machine-learning-go-client v0.7.1-0.20240702191547-8b1f45f0374c/go.mod h1:9xRIoH6Y6RubuCPNjLfpckE/fLVe9dazg3HSLI1ARAU=
+github.com/grafana/machine-learning-go-client v0.7.1-0.20240703190259-47c2986b5066 h1:eODY6pbanmIfNDC5tJ76zknDjbXAZS5OOMUXLSXjrBw=
+github.com/grafana/machine-learning-go-client v0.7.1-0.20240703190259-47c2986b5066/go.mod h1:9xRIoH6Y6RubuCPNjLfpckE/fLVe9dazg3HSLI1ARAU=
 github.com/grafana/otel-profiling-go v0.5.1 h1:stVPKAFZSa7eGiqbYuG25VcqYksR6iWvF3YH66t4qL8=
 github.com/grafana/otel-profiling-go v0.5.1/go.mod h1:ftN/t5A/4gQI19/8MoWurBEtC6gFw8Dns1sJZ9W4Tls=
 github.com/grafana/pyroscope-go/godeltaprof v0.1.7 h1:C11j63y7gymiW8VugJ9ZW0pWfxTZugdSJyC48olk5KY=

internal/resources/machinelearning/resource_alert.go

@@ -0,0 +1,215 @@
+package machinelearning
+
+import (
+	"context"
+
+	"github.com/grafana/machine-learning-go-client/mlapi"
+	"github.com/grafana/terraform-provider-grafana/v3/internal/common"
+	"github.com/hashicorp/terraform-plugin-sdk/v2/diag"
+	"github.com/hashicorp/terraform-plugin-sdk/v2/helper/schema"
+	"github.com/hashicorp/terraform-plugin-sdk/v2/helper/validation"
+	"github.com/prometheus/common/model"
+)
+
+var resourceAlertID = common.NewResourceID(common.StringIDField("id"))
+
+func resourceAlert() *common.Resource {
+	schema := &schema.Resource{
+
+		Description: `
+A job defines the queries and model parameters for a machine learning task.
+`,
+
+		CreateContext: checkClient(resourceAlertCreate),
+		ReadContext:   checkClient(resourceAlertRead),
+		UpdateContext: checkClient(resourceAlertUpdate),
+		DeleteContext: checkClient(resourceAlertDelete),
+		Importer: &schema.ResourceImporter{
+			StateContext: schema.ImportStatePassthroughContext,
+		},
+
+		Schema: map[string]*schema.Schema{
+			"job": {
+				Description:  "The forecast this alert belongs to.",
+				Type:         schema.TypeString,
+				Optional:     true,
+				ForceNew:     true,
+				ExactlyOneOf: []string{"job", "outlier"},
+			},
+			"outlier": {
+				Description:  "The forecast this alert belongs to.",
+				Type:         schema.TypeString,
+				Optional:     true,
+				ForceNew:     true,
+				ExactlyOneOf: []string{"job", "outlier"},
+			},
+			"id": {
+				Description: "The ID of the alert.",
+				Type:        schema.TypeString,
+				Computed:    true,
+			},
+			"title": {
+				Description: "The title of the alert.",
+				Type:        schema.TypeString,
+				Required:    true,
+			},
+			"anomaly_condition": {
+				Description:  "The condition for when to consider a point as anomalous.",
+				Type:         schema.TypeString,
+				Optional:     true,
+				ValidateFunc: validation.StringInSlice([]string{"any", "low", "high"}, false),
+			},
+			"for": {
+				Description: "How long values must be anomalous before firing an alert.",
+				Type:        schema.TypeString,
+				Optional:    true,
+			},
+			"threshold": {
+				Description: "The threshold of points over the window that need to be anomalous to alert.",
+				Type:        schema.TypeString,
+				Optional:    true,
+			},
+			"window": {
+				Description: "How much time to average values over",
+				Type:        schema.TypeString,
+				Optional:    true,
+			},
+			"labels": {
+				Description: "Labels to add to the alert generated in Grafana.",
+				Type:        schema.TypeMap,
+				Optional:    true,
+			},
+			"annotations": {
+				Description: "Annotations to add to the alert generated in Grafana.",
+				Type:        schema.TypeMap,
+				Optional:    true,
+			},
+			"no_data_state": {
+				Description:  "How the alert should be processed when no data is returned by the underlying series",
+				Type:         schema.TypeString,
+				Optional:     true,
+				ValidateFunc: validation.StringInSlice([]string{"Alerting", "NoData", "OK"}, false),
+			},
+		},
+	}
+
+	return common.NewLegacySDKResource(
+		common.CategoryMachineLearning,
+		"grafana_machine_learning_alert",
+		resourceAlertID,
+		schema,
+	)
+}
+
+func resourceAlertCreate(ctx context.Context, d *schema.ResourceData, meta interface{}) diag.Diagnostics {
+	c := meta.(*common.Client).MLAPI
+	alert, err := makeMLAlert(d)
+	if err != nil {
+		return diag.FromErr(err)
+	}
+	jobID := d.Get("job").(string)
+	if jobID != "" {
+		alert, err = c.NewJobAlert(ctx, jobID, alert)
+	} else {
+		outlierID := d.Get("outlier").(string)
+		alert, err = c.NewOutlierAlert(ctx, outlierID, alert)
+	}
+	if err != nil {
+		return diag.FromErr(err)
+	}
+	d.SetId(alert.ID)
+	return resourceAlertRead(ctx, d, meta)
+}
+
+func resourceAlertRead(ctx context.Context, d *schema.ResourceData, meta interface{}) diag.Diagnostics {
+	c := meta.(*common.Client).MLAPI
+	var (
+		alert mlapi.Alert
+		err   error
+	)
+	jobID := d.Get("job").(string)
+	if jobID != "" {
+		alert, err = c.JobAlert(ctx, jobID, d.Id())
+	} else {
+		outlierID := d.Get("outlier").(string)
+		alert, err = c.OutlierAlert(ctx, outlierID, d.Id())
+	}
+
+	if err, shouldReturn := common.CheckReadError("alert", d, err); shouldReturn {
+		return err
+	}
+
+	d.Set("title", alert.Title)
+	d.Set("anomaly_condition", alert.AnomalyCondition)
+	d.Set("for", alert.For)
+	d.Set("threshold", alert.Threshold)
+	d.Set("window", alert.Window)
+	d.Set("labels", alert.Labels)
+	d.Set("annotations", alert.Annotations)
+	d.Set("no_data_state", alert.NoDataState)
+
+	return nil
+}
+
+func resourceAlertUpdate(ctx context.Context, d *schema.ResourceData, meta interface{}) diag.Diagnostics {
+	c := meta.(*common.Client).MLAPI
+	alert, err := makeMLAlert(d)
+	if err != nil {
+		return diag.FromErr(err)
+	}
+	jobID := d.Get("job").(string)
+	if jobID != "" {
+		_, err = c.UpdateJobAlert(ctx, jobID, alert)
+	} else {
+		outlierID := d.Get("outlier").(string)
+		_, err = c.UpdateOutlierAlert(ctx, outlierID, alert)
+	}
+
+	if err != nil {
+		return diag.FromErr(err)
+	}
+	return resourceAlertRead(ctx, d, meta)
+}
+
+func resourceAlertDelete(ctx context.Context, d *schema.ResourceData, meta interface{}) diag.Diagnostics {
+	c := meta.(*common.Client).MLAPI
+	jobID := d.Get("job").(string)
+	var err error
+	if jobID != "" {
+		err = c.DeleteJobAlert(ctx, jobID, d.Id())
+	} else {
+		outlierID := d.Get("outlier").(string)
+		err = c.DeleteOutlierAlert(ctx, outlierID, d.Id())
+	}
+	return diag.FromErr(err)
+}
+
+func makeMLAlert(d *schema.ResourceData) (mlapi.Alert, error) {
+	forClause, err := model.ParseDuration(d.Get("for").(string))
+	if err != nil {
+		return mlapi.Alert{}, err
+	}
+	window, err := model.ParseDuration(d.Get("window").(string))
+	if err != nil {
+		return mlapi.Alert{}, err
+	}
+	labels := map[string]string{}
+	for k, v := range d.Get("labels").(map[string]interface{}) {
+		labels[k] = v.(string)
+	}
+	annotations := map[string]string{}
+	for k, v := range d.Get("annotations").(map[string]interface{}) {
+		annotations[k] = v.(string)
+	}
+	return mlapi.Alert{
+		ID:               d.Id(),
+		Title:            d.Get("title").(string),
+		AnomalyCondition: mlapi.AnomalyCondition(d.Get("anomaly_condition").(string)),
+		For:              forClause,
+		Threshold:        d.Get("threshold").(string),
+		Window:           window,
+		Labels:           labels,
+		Annotations:      annotations,
+		NoDataState:      mlapi.NoDataState(d.Get("no_data_state").(string)),
+	}, nil
+}