AzureMonitor: Alerting for Azure Application Insights (#19381)

* Convert Azure Application Insights datasource to Go

Allows for alerting of Application Insights data source

Closes: #15153

* Fix timeGrainReset

* Default time interval for querys for alerts

* Fix a few rename related bugs

* Update readme to indicate App Insights alerting

* Fix typo and add tests to ensure migration is happening

* Address code review feedback (mostly typos and unintended changes)

docs/sources/features/datasources/azuremonitor.md

@@ -216,7 +216,9 @@ Examples:
 
 ### Application Insights Alerting
 
-Not implemented yet.
+Grafana alerting is supported for Application Insights. This is not Azure Alerts support. Read more about how alerting in Grafana works [here]({{< relref "alerting/rules.md" >}}).
+
+{{< docs-imagebox img="/img/docs/v60/azuremonitor-alerting.png" class="docs-image--no-shadow" caption="Azure Monitor Alerting" >}}
 
 ## Querying the Azure Log Analytics Service
 

pkg/tsdb/azuremonitor/applicationinsights-datasource.go

@@ -0,0 +1,592 @@
+package azuremonitor
+
+import (
+	"context"
+	"encoding/json"
+	"errors"
+	"fmt"
+	"github.com/grafana/grafana/pkg/api/pluginproxy"
+	"github.com/grafana/grafana/pkg/components/null"
+	"github.com/grafana/grafana/pkg/components/simplejson"
+	"github.com/grafana/grafana/pkg/models"
+	"github.com/grafana/grafana/pkg/plugins"
+	"github.com/grafana/grafana/pkg/setting"
+	"github.com/grafana/grafana/pkg/tsdb"
+	"github.com/opentracing/opentracing-go"
+	"golang.org/x/net/context/ctxhttp"
+	"io/ioutil"
+	"net/http"
+	"net/url"
+	"path"
+	"strings"
+	"time"
+)
+
+// ApplicationInsightsDatasource calls the application insights query API's
+type ApplicationInsightsDatasource struct {
+	httpClient *http.Client
+	dsInfo     *models.DataSource
+}
+
+type ApplicationInsightsQuery struct {
+	RefID string
+
+	IsRaw bool
+
+	// Text based raw query options
+	ApiURL            string
+	Params            url.Values
+	Alias             string
+	Target            string
+	TimeColumnName    string
+	ValueColumnName   string
+	SegmentColumnName string
+}
+
+func (e *ApplicationInsightsDatasource) executeTimeSeriesQuery(ctx context.Context, originalQueries []*tsdb.Query, timeRange *tsdb.TimeRange) (*tsdb.Response, error) {
+	result := &tsdb.Response{
+		Results: map[string]*tsdb.QueryResult{},
+	}
+
+	queries, err := e.buildQueries(originalQueries, timeRange)
+	if err != nil {
+		return nil, err
+	}
+
+	for _, query := range queries {
+		queryRes, err := e.executeQuery(ctx, query)
+		if err != nil {
+			return nil, err
+		}
+		result.Results[query.RefID] = queryRes
+	}
+
+	return result, nil
+}
+
+func (e *ApplicationInsightsDatasource) buildQueries(queries []*tsdb.Query, timeRange *tsdb.TimeRange) ([]*ApplicationInsightsQuery, error) {
+	applicationInsightsQueries := []*ApplicationInsightsQuery{}
+	startTime, err := timeRange.ParseFrom()
+	if err != nil {
+		return nil, err
+	}
+
+	endTime, err := timeRange.ParseTo()
+	if err != nil {
+		return nil, err
+	}
+
+	for _, query := range queries {
+		applicationInsightsTarget := query.Model.Get("appInsights").MustMap()
+		azlog.Debug("Application Insights", "target", applicationInsightsTarget)
+
+		rawQuery := false
+		if asInterface, ok := applicationInsightsTarget["rawQuery"]; ok {
+			if asBool, ok := asInterface.(bool); ok {
+				rawQuery = asBool
+			} else {
+				return nil, errors.New("'rawQuery' should be a boolean")
+			}
+		} else {
+			return nil, errors.New("missing 'rawQuery' property")
+		}
+
+		if rawQuery {
+			var rawQueryString string
+			if asInterface, ok := applicationInsightsTarget["rawQueryString"]; ok {
+				if asString, ok := asInterface.(string); ok {
+					rawQueryString = asString
+				}
+			}
+			if rawQueryString == "" {
+				return nil, errors.New("rawQuery requires rawQueryString")
+			}
+
+			rawQueryString, err := KqlInterpolate(query, timeRange, fmt.Sprintf("%v", rawQueryString))
+			if err != nil {
+				return nil, err
+			}
+
+			params := url.Values{}
+			params.Add("query", rawQueryString)
+
+			applicationInsightsQueries = append(applicationInsightsQueries, &ApplicationInsightsQuery{
+				RefID:             query.RefId,
+				IsRaw:             true,
+				ApiURL:            "query",
+				Params:            params,
+				TimeColumnName:    fmt.Sprintf("%v", applicationInsightsTarget["timeColumn"]),
+				ValueColumnName:   fmt.Sprintf("%v", applicationInsightsTarget["valueColumn"]),
+				SegmentColumnName: fmt.Sprintf("%v", applicationInsightsTarget["segmentColumn"]),
+				Target:            params.Encode(),
+			})
+		} else {
+			alias := ""
+			if val, ok := applicationInsightsTarget["alias"]; ok {
+				alias = fmt.Sprintf("%v", val)
+			}
+
+			azureURL := fmt.Sprintf("metrics/%s", fmt.Sprintf("%v", applicationInsightsTarget["metricName"]))
+			timeGrain := fmt.Sprintf("%v", applicationInsightsTarget["timeGrain"])
+			timeGrains := applicationInsightsTarget["allowedTimeGrainsMs"]
+			if timeGrain == "auto" {
+				timeGrain, err = setAutoTimeGrain(query.IntervalMs, timeGrains)
+				if err != nil {
+					return nil, err
+				}
+			}
+
+			params := url.Values{}
+			params.Add("timespan", fmt.Sprintf("%v/%v", startTime.UTC().Format(time.RFC3339), endTime.UTC().Format(time.RFC3339)))
+			if timeGrain != "none" {
+				params.Add("interval", timeGrain)
+			}
+			params.Add("aggregation", fmt.Sprintf("%v", applicationInsightsTarget["aggregation"]))
+
+			dimension := strings.TrimSpace(fmt.Sprintf("%v", applicationInsightsTarget["dimension"]))
+			if applicationInsightsTarget["dimension"] != nil && len(dimension) > 0 && !strings.EqualFold(dimension, "none") {
+				params.Add("segment", dimension)
+			}
+
+			dimensionFilter := strings.TrimSpace(fmt.Sprintf("%v", applicationInsightsTarget["dimensionFilter"]))
+			if applicationInsightsTarget["dimensionFilter"] != nil && len(dimensionFilter) > 0 {
+				params.Add("filter", fmt.Sprintf("%v", dimensionFilter))
+			}
+
+			applicationInsightsQueries = append(applicationInsightsQueries, &ApplicationInsightsQuery{
+				RefID:  query.RefId,
+				IsRaw:  false,
+				ApiURL: azureURL,
+				Params: params,
+				Alias:  alias,
+				Target: params.Encode(),
+			})
+		}
+	}
+
+	return applicationInsightsQueries, nil
+}
+
+func (e *ApplicationInsightsDatasource) executeQuery(ctx context.Context, query *ApplicationInsightsQuery) (*tsdb.QueryResult, error) {
+	queryResult := &tsdb.QueryResult{Meta: simplejson.New(), RefId: query.RefID}
+
+	req, err := e.createRequest(ctx, e.dsInfo)
+	if err != nil {
+		queryResult.Error = err
+		return queryResult, nil
+	}
+
+	req.URL.Path = path.Join(req.URL.Path, query.ApiURL)
+	req.URL.RawQuery = query.Params.Encode()
+
+	span, ctx := opentracing.StartSpanFromContext(ctx, "application insights query")
+	span.SetTag("target", query.Target)
+	span.SetTag("datasource_id", e.dsInfo.Id)
+	span.SetTag("org_id", e.dsInfo.OrgId)
+
+	defer span.Finish()
+
+	err = opentracing.GlobalTracer().Inject(
+		span.Context(),
+		opentracing.HTTPHeaders,
+		opentracing.HTTPHeadersCarrier(req.Header))
+
+	if err != nil {
+		azlog.Warn("failed to inject global tracer")
+	}
+
+	azlog.Debug("ApplicationInsights", "Request URL", req.URL.String())
+	res, err := ctxhttp.Do(ctx, e.httpClient, req)
+	if err != nil {
+		queryResult.Error = err
+		return queryResult, nil
+	}
+
+	body, err := ioutil.ReadAll(res.Body)
+	defer res.Body.Close()
+	if err != nil {
+		return nil, err
+	}
+
+	if res.StatusCode/100 != 2 {
+		azlog.Error("Request failed", "status", res.Status, "body", string(body))
+		return nil, fmt.Errorf(string(body))
+	}
+
+	if query.IsRaw {
+		queryResult.Series, queryResult.Meta, err = e.parseTimeSeriesFromQuery(body, query)
+		if err != nil {
+			queryResult.Error = err
+			return queryResult, nil
+		}
+	} else {
+		queryResult.Series, err = e.parseTimeSeriesFromMetrics(body, query)
+		if err != nil {
+			queryResult.Error = err
+			return queryResult, nil
+		}
+	}
+
+	return queryResult, nil
+}
+
+func (e *ApplicationInsightsDatasource) createRequest(ctx context.Context, dsInfo *models.DataSource) (*http.Request, error) {
+	// find plugin
+	plugin, ok := plugins.DataSources[dsInfo.Type]
+	if !ok {
+		return nil, errors.New("Unable to find datasource plugin Azure Application Insights")
+	}
+
+	var appInsightsRoute *plugins.AppPluginRoute
+	for _, route := range plugin.Routes {
+		if route.Path == "appinsights" {
+			appInsightsRoute = route
+			break
+		}
+	}
+
+	appInsightsAppId := dsInfo.JsonData.Get("appInsightsAppId").MustString()
+	proxyPass := fmt.Sprintf("appinsights/v1/apps/%s", appInsightsAppId)
+
+	u, _ := url.Parse(dsInfo.Url)
+	u.Path = path.Join(u.Path, fmt.Sprintf("/v1/apps/%s", appInsightsAppId))
+
+	req, err := http.NewRequest(http.MethodGet, u.String(), nil)
+	if err != nil {
+		azlog.Error("Failed to create request", "error", err)
+		return nil, fmt.Errorf("Failed to create request. error: %v", err)
+	}
+
+	req.Header.Set("User-Agent", fmt.Sprintf("Grafana/%s", setting.BuildVersion))
+
+	pluginproxy.ApplyRoute(ctx, req, proxyPass, appInsightsRoute, dsInfo)
+
+	return req, nil
+}
+
+func (e *ApplicationInsightsDatasource) parseTimeSeriesFromQuery(body []byte, query *ApplicationInsightsQuery) (tsdb.TimeSeriesSlice, *simplejson.Json, error) {
+	var data ApplicationInsightsQueryResponse
+	err := json.Unmarshal(body, &data)
+	if err != nil {
+		azlog.Error("Failed to unmarshal Application Insights response", "error", err, "body", string(body))
+		return nil, nil, err
+	}
+
+	type Metadata struct {
+		Columns []string `json:"columns"`
+	}
+
+	meta := Metadata{}
+
+	for _, t := range data.Tables {
+		if t.Name == "PrimaryResult" {
+			timeIndex, valueIndex, segmentIndex := -1, -1, -1
+			meta.Columns = make([]string, 0)
+			for i, v := range t.Columns {
+				meta.Columns = append(meta.Columns, v.Name)
+				switch v.Name {
+				case query.TimeColumnName:
+					timeIndex = i
+				case query.ValueColumnName:
+					valueIndex = i
+				case query.SegmentColumnName:
+					segmentIndex = i
+				}
+			}
+
+			if timeIndex == -1 {
+				azlog.Info("no time column specified, returning existing columns, no data")
+				return nil, simplejson.NewFromAny(meta), nil
+			}
+
+			if valueIndex == -1 {
+				azlog.Info("no value column specified, returning existing columns, no data")
+				return nil, simplejson.NewFromAny(meta), nil
+			}
+
+			var getPoints func([]interface{}) *tsdb.TimeSeriesPoints
+			slice := tsdb.TimeSeriesSlice{}
+			if segmentIndex == -1 {
+				legend := formatApplicationInsightsLegendKey(query.Alias, query.ValueColumnName, "", "")
+				series := tsdb.NewTimeSeries(legend, []tsdb.TimePoint{})
+				slice = append(slice, series)
+				getPoints = func(row []interface{}) *tsdb.TimeSeriesPoints {
+					return &series.Points
+				}
+			} else {
+				mapping := map[string]*tsdb.TimeSeriesPoints{}
+				getPoints = func(row []interface{}) *tsdb.TimeSeriesPoints {
+					segment := fmt.Sprintf("%v", row[segmentIndex])
+					if points, ok := mapping[segment]; ok {
+						return points
+					}
+					legend := formatApplicationInsightsLegendKey(query.Alias, query.ValueColumnName, query.SegmentColumnName, segment)
+					series := tsdb.NewTimeSeries(legend, []tsdb.TimePoint{})
+					slice = append(slice, series)
+					mapping[segment] = &series.Points
+					return &series.Points
+				}
+			}
+
+			for _, r := range t.Rows {
+				timeStr, ok := r[timeIndex].(string)
+				if !ok {
+					return nil, simplejson.NewFromAny(meta), errors.New("invalid time value")
+				}
+				timeValue, err := time.Parse(time.RFC3339Nano, timeStr)
+				if err != nil {
+					return nil, simplejson.NewFromAny(meta), err
+				}
+
+				var value float64
+				if value, err = getFloat(r[valueIndex]); err != nil {
+					return nil, simplejson.NewFromAny(meta), err
+				}
+
+				points := getPoints(r)
+				*points = append(*points, tsdb.NewTimePoint(null.FloatFrom(value), float64(timeValue.Unix()*1000)))
+			}
+
+			return slice, simplejson.NewFromAny(meta), nil
+		}
+	}
+
+	return nil, nil, errors.New("could not find table")
+}
+
+func (e *ApplicationInsightsDatasource) parseTimeSeriesFromMetrics(body []byte, query *ApplicationInsightsQuery) (tsdb.TimeSeriesSlice, error) {
+	doc, err := simplejson.NewJson(body)
+	if err != nil {
+		return nil, err
+	}
+
+	value := doc.Get("value").MustMap()
+
+	if value == nil {
+		return nil, errors.New("could not find value element")
+	}
+
+	endStr, ok := value["end"].(string)
+	if !ok {
+		return nil, errors.New("missing 'end' value in response")
+	}
+	endTime, err := time.Parse(time.RFC3339Nano, endStr)
+	if err != nil {
+		return nil, fmt.Errorf("bad 'end' value: %v", err)
+	}
+
+	for k, v := range value {
+		switch k {
+		case "start":
+		case "end":
+		case "interval":
+		case "segments":
+			// we have segments!
+			return parseSegmentedValueTimeSeries(query, endTime, v)
+		default:
+			return parseSingleValueTimeSeries(query, k, endTime, v)
+		}
+	}
+
+	azlog.Error("Bad response from application insights/metrics", "body", string(body))
+	return nil, errors.New("could not find expected values in response")
+}
+
+func parseSegmentedValueTimeSeries(query *ApplicationInsightsQuery, endTime time.Time, segmentsJson interface{}) (tsdb.TimeSeriesSlice, error) {
+	segments, ok := segmentsJson.([]interface{})
+	if !ok {
+		return nil, errors.New("bad segments value")
+	}
+
+	slice := tsdb.TimeSeriesSlice{}
+	seriesMap := map[string]*tsdb.TimeSeriesPoints{}
+
+	for _, segment := range segments {
+		segmentMap, ok := segment.(map[string]interface{})
+		if !ok {
+			return nil, errors.New("bad segments value")
+		}
+		err := processSegment(&slice, segmentMap, query, endTime, seriesMap)
+		if err != nil {
+			return nil, err
+		}
+	}
+
+	return slice, nil
+}
+
+func processSegment(slice *tsdb.TimeSeriesSlice, segment map[string]interface{}, query *ApplicationInsightsQuery, endTime time.Time, pointMap map[string]*tsdb.TimeSeriesPoints) error {
+	var segmentName string
+	var segmentValue string
+	var childSegments []interface{}
+	hasChildren := false
+	var value float64
+	var valueName string
+	var ok bool
+	var err error
+	for k, v := range segment {
+		switch k {
+		case "start":
+		case "end":
+			endStr, ok := v.(string)
+			if !ok {
+				return errors.New("missing 'end' value in response")
+			}
+			endTime, err = time.Parse(time.RFC3339Nano, endStr)
+			if err != nil {
+				return fmt.Errorf("bad 'end' value: %v", err)
+			}
+		case "segments":
+			childSegments, ok = v.([]interface{})
+			if !ok {
+				return errors.New("invalid format segments")
+			}
+			hasChildren = true
+		default:
+			mapping, hasValues := v.(map[string]interface{})
+			if hasValues {
+				valueName = k
+				value, err = getAggregatedValue(mapping, valueName)
+				if err != nil {
+					return err
+				}
+			} else {
+				segmentValue, ok = v.(string)
+				if !ok {
+					return fmt.Errorf("invalid mapping for key %v", k)
+				}
+				segmentName = k
+			}
+		}
+	}
+
+	if hasChildren {
+		for _, s := range childSegments {
+			segmentMap, ok := s.(map[string]interface{})
+			if !ok {
+				return errors.New("invalid format segments")
+			}
+			if err := processSegment(slice, segmentMap, query, endTime, pointMap); err != nil {
+				return err
+			}
+		}
+	} else {
+
+		aliased := formatApplicationInsightsLegendKey(query.Alias, valueName, segmentName, segmentValue)
+
+		if segmentValue == "" {
+			segmentValue = valueName
+		}
+
+		points, ok := pointMap[segmentValue]
+
+		if !ok {
+			series := tsdb.NewTimeSeries(aliased, tsdb.TimeSeriesPoints{})
+			points = &series.Points
+			*slice = append(*slice, series)
+			pointMap[segmentValue] = points
+		}
+
+		*points = append(*points, tsdb.NewTimePoint(null.FloatFrom(value), float64(endTime.Unix()*1000)))
+	}
+
+	return nil
+}
+
+func parseSingleValueTimeSeries(query *ApplicationInsightsQuery, metricName string, endTime time.Time, valueJson interface{}) (tsdb.TimeSeriesSlice, error) {
+	legend := formatApplicationInsightsLegendKey(query.Alias, metricName, "", "")
+
+	valueMap, ok := valueJson.(map[string]interface{})
+	if !ok {
+		return nil, errors.New("bad value aggregation")
+	}
+
+	metricValue, err := getAggregatedValue(valueMap, metricName)
+	if err != nil {
+		return nil, err
+	}
+
+	return []*tsdb.TimeSeries{
+		tsdb.NewTimeSeries(
+			legend,
+			tsdb.TimeSeriesPoints{
+				tsdb.NewTimePoint(
+					null.FloatFrom(metricValue),
+					float64(endTime.Unix()*1000)),
+			},
+		),
+	}, nil
+}
+
+func getAggregatedValue(valueMap map[string]interface{}, valueName string) (float64, error) {
+
+	aggValue := ""
+	var metricValue float64
+	var err error
+	for k, v := range valueMap {
+		if aggValue != "" {
+			return 0, fmt.Errorf("found multiple aggregations, %v, %v", aggValue, k)
+		}
+		if k == "" {
+			return 0, errors.New("found no aggregation name")
+		}
+		aggValue = k
+		metricValue, err = getFloat(v)
+
+		if err != nil {
+			return 0, fmt.Errorf("bad value: %v", err)
+		}
+	}
+
+	if aggValue == "" {
+		return 0, fmt.Errorf("no aggregation value found for %v", valueName)
+	}
+
+	return metricValue, nil
+}
+
+func getFloat(in interface{}) (float64, error) {
+	if out, ok := in.(float32); ok {
+		return float64(out), nil
+	} else if out, ok := in.(int32); ok {
+		return float64(out), nil
+	} else if out, ok := in.(json.Number); ok {
+		return out.Float64()
+	} else if out, ok := in.(int64); ok {
+		return float64(out), nil
+	} else if out, ok := in.(float64); ok {
+		return out, nil
+	}
+
+	return 0, fmt.Errorf("cannot convert '%v' to float32", in)
+}
+
+// formatApplicationInsightsLegendKey builds the legend key or timeseries name
+// Alias patterns like {{resourcename}} are replaced with the appropriate data values.
+func formatApplicationInsightsLegendKey(alias string, metricName string, dimensionName string, dimensionValue string) string {
+	if alias == "" {
+		if len(dimensionName) > 0 {
+			return fmt.Sprintf("{%s=%s}.%s", dimensionName, dimensionValue, metricName)
+		}
+		return metricName
+	}
+
+	result := legendKeyFormat.ReplaceAllFunc([]byte(alias), func(in []byte) []byte {
+		metaPartName := strings.Replace(string(in), "{{", "", 1)
+		metaPartName = strings.Replace(metaPartName, "}}", "", 1)
+		metaPartName = strings.ToLower(strings.TrimSpace(metaPartName))
+
+		switch metaPartName {
+		case "metric":
+			return []byte(metricName)
+		case "dimensionname", "groupbyname":
+			return []byte(dimensionName)
+		case "dimensionvalue", "groupbyvalue":
+			return []byte(dimensionValue)
+		}
+
+		return in
+	})
+
+	return string(result)
+}

pkg/tsdb/azuremonitor/applicationinsights-datasource_test.go

@@ -0,0 +1,316 @@
+package azuremonitor
+
+import (
+	"encoding/json"
+	"fmt"
+	"io/ioutil"
+	"testing"
+	"time"
+
+	"github.com/grafana/grafana/pkg/components/simplejson"
+	"github.com/grafana/grafana/pkg/models"
+	"github.com/grafana/grafana/pkg/tsdb"
+
+	. "github.com/smartystreets/goconvey/convey"
+)
+
+func TestApplicationInsightsDatasource(t *testing.T) {
+	Convey("ApplicationInsightsDatasource", t, func() {
+		datasource := &ApplicationInsightsDatasource{}
+
+		Convey("Parse queries from frontend and build AzureMonitor API queries", func() {
+			fromStart := time.Date(2018, 3, 15, 13, 0, 0, 0, time.UTC).In(time.Local)
+			tsdbQuery := &tsdb.TsdbQuery{
+				TimeRange: &tsdb.TimeRange{
+					From: fmt.Sprintf("%v", fromStart.Unix()*1000),
+					To:   fmt.Sprintf("%v", fromStart.Add(34*time.Minute).Unix()*1000),
+				},
+				Queries: []*tsdb.Query{
+					{
+						DataSource: &models.DataSource{
+							JsonData: simplejson.NewFromAny(map[string]interface{}{}),
+						},
+						Model: simplejson.NewFromAny(map[string]interface{}{
+							"appInsights": map[string]interface{}{
+								"rawQuery":    false,
+								"timeGrain":   "PT1M",
+								"aggregation": "Average",
+								"metricName":  "server/exceptions",
+								"alias":       "testalias",
+								"queryType":   "Application Insights",
+							},
+						}),
+						RefId:      "A",
+						IntervalMs: 1234,
+					},
+				},
+			}
+			Convey("and is a normal query", func() {
+				queries, err := datasource.buildQueries(tsdbQuery.Queries, tsdbQuery.TimeRange)
+				So(err, ShouldBeNil)
+
+				So(len(queries), ShouldEqual, 1)
+				So(queries[0].RefID, ShouldEqual, "A")
+				So(queries[0].ApiURL, ShouldEqual, "metrics/server/exceptions")
+				So(queries[0].Target, ShouldEqual, "aggregation=Average&interval=PT1M&timespan=2018-03-15T13%3A00%3A00Z%2F2018-03-15T13%3A34%3A00Z")
+				So(len(queries[0].Params), ShouldEqual, 3)
+				So(queries[0].Params["timespan"][0], ShouldEqual, "2018-03-15T13:00:00Z/2018-03-15T13:34:00Z")
+				So(queries[0].Params["aggregation"][0], ShouldEqual, "Average")
+				So(queries[0].Params["interval"][0], ShouldEqual, "PT1M")
+				So(queries[0].Alias, ShouldEqual, "testalias")
+			})
+
+			Convey("and has a time grain set to auto", func() {
+				tsdbQuery.Queries[0].Model = simplejson.NewFromAny(map[string]interface{}{
+					"appInsights": map[string]interface{}{
+						"rawQuery":    false,
+						"timeGrain":   "auto",
+						"aggregation": "Average",
+						"metricName":  "Percentage CPU",
+						"alias":       "testalias",
+						"queryType":   "Application Insights",
+					},
+				})
+				tsdbQuery.Queries[0].IntervalMs = 400000
+
+				queries, err := datasource.buildQueries(tsdbQuery.Queries, tsdbQuery.TimeRange)
+				So(err, ShouldBeNil)
+
+				So(queries[0].Params["interval"][0], ShouldEqual, "PT15M")
+			})
+
+			Convey("and has a time grain set to auto and the metric has a limited list of allowed time grains", func() {
+				tsdbQuery.Queries[0].Model = simplejson.NewFromAny(map[string]interface{}{
+					"appInsights": map[string]interface{}{
+						"rawQuery":            false,
+						"timeGrain":           "auto",
+						"aggregation":         "Average",
+						"metricName":          "Percentage CPU",
+						"alias":               "testalias",
+						"queryType":           "Application Insights",
+						"allowedTimeGrainsMs": []interface{}{"auto", json.Number("60000"), json.Number("300000")},
+					},
+				})
+				tsdbQuery.Queries[0].IntervalMs = 400000
+
+				queries, err := datasource.buildQueries(tsdbQuery.Queries, tsdbQuery.TimeRange)
+				So(err, ShouldBeNil)
+
+				So(queries[0].Params["interval"][0], ShouldEqual, "PT5M")
+			})
+
+			Convey("and has a dimension filter", func() {
+				tsdbQuery.Queries[0].Model = simplejson.NewFromAny(map[string]interface{}{
+					"appInsights": map[string]interface{}{
+						"rawQuery":        false,
+						"timeGrain":       "PT1M",
+						"aggregation":     "Average",
+						"metricName":      "Percentage CPU",
+						"alias":           "testalias",
+						"queryType":       "Application Insights",
+						"dimension":       "blob",
+						"dimensionFilter": "blob eq '*'",
+					},
+				})
+
+				queries, err := datasource.buildQueries(tsdbQuery.Queries, tsdbQuery.TimeRange)
+				So(err, ShouldBeNil)
+
+				So(queries[0].Target, ShouldEqual, "aggregation=Average&filter=blob+eq+%27%2A%27&interval=PT1M&segment=blob&timespan=2018-03-15T13%3A00%3A00Z%2F2018-03-15T13%3A34%3A00Z")
+				So(queries[0].Params["filter"][0], ShouldEqual, "blob eq '*'")
+
+			})
+
+			Convey("and has a dimension filter set to None", func() {
+				tsdbQuery.Queries[0].Model = simplejson.NewFromAny(map[string]interface{}{
+					"appInsights": map[string]interface{}{
+						"rawQuery":    false,
+						"timeGrain":   "PT1M",
+						"aggregation": "Average",
+						"metricName":  "Percentage CPU",
+						"alias":       "testalias",
+						"queryType":   "Application Insights",
+						"dimension":   "None",
+					},
+				})
+
+				queries, err := datasource.buildQueries(tsdbQuery.Queries, tsdbQuery.TimeRange)
+				So(err, ShouldBeNil)
+
+				So(queries[0].Target, ShouldEqual, "aggregation=Average&interval=PT1M&timespan=2018-03-15T13%3A00%3A00Z%2F2018-03-15T13%3A34%3A00Z")
+			})
+
+			Convey("id a raw query", func() {
+				tsdbQuery.Queries[0].Model = simplejson.NewFromAny(map[string]interface{}{
+					"appInsights": map[string]interface{}{
+						"rawQuery":       true,
+						"rawQueryString": "exceptions | where $__timeFilter(timestamp) | summarize count=count() by bin(timestamp, $__interval)",
+						"timeColumn":     "timestamp",
+						"valueColumn":    "count",
+					},
+				})
+
+				queries, err := datasource.buildQueries(tsdbQuery.Queries, tsdbQuery.TimeRange)
+				So(err, ShouldBeNil)
+				So(queries[0].Params["query"][0], ShouldEqual, "exceptions | where ['timestamp'] >= datetime('2018-03-15T13:00:00Z') and ['timestamp'] <= datetime('2018-03-15T13:34:00Z') | summarize count=count() by bin(timestamp, 1234ms)")
+				So(queries[0].Target, ShouldEqual, "query=exceptions+%7C+where+%5B%27timestamp%27%5D+%3E%3D+datetime%28%272018-03-15T13%3A00%3A00Z%27%29+and+%5B%27timestamp%27%5D+%3C%3D+datetime%28%272018-03-15T13%3A34%3A00Z%27%29+%7C+summarize+count%3Dcount%28%29+by+bin%28timestamp%2C+1234ms%29")
+			})
+		})
+
+		Convey("Parse Application Insights query API response in the time series format", func() {
+			Convey("no segments", func() {
+				data, err := ioutil.ReadFile("./test-data/applicationinsights/1-application-insights-response-raw-query.json")
+				So(err, ShouldBeNil)
+
+				query := &ApplicationInsightsQuery{
+					IsRaw:           true,
+					TimeColumnName:  "timestamp",
+					ValueColumnName: "value",
+				}
+				series, _, err := datasource.parseTimeSeriesFromQuery(data, query)
+				So(err, ShouldBeNil)
+
+				So(len(series), ShouldEqual, 1)
+				So(series[0].Name, ShouldEqual, "value")
+				So(len(series[0].Points), ShouldEqual, 2)
+
+				So(series[0].Points[0][0].Float64, ShouldEqual, 1)
+				So(series[0].Points[0][1].Float64, ShouldEqual, int64(1568336523000))
+
+				So(series[0].Points[1][0].Float64, ShouldEqual, 2)
+				So(series[0].Points[1][1].Float64, ShouldEqual, int64(1568340123000))
+			})
+
+			Convey("with segments", func() {
+				data, err := ioutil.ReadFile("./test-data/applicationinsights/2-application-insights-response-raw-query-segmented.json")
+				So(err, ShouldBeNil)
+
+				query := &ApplicationInsightsQuery{
+					IsRaw:             true,
+					TimeColumnName:    "timestamp",
+					ValueColumnName:   "value",
+					SegmentColumnName: "segment",
+				}
+				series, _, err := datasource.parseTimeSeriesFromQuery(data, query)
+				So(err, ShouldBeNil)
+
+				So(len(series), ShouldEqual, 2)
+				So(series[0].Name, ShouldEqual, "{segment=a}.value")
+				So(len(series[0].Points), ShouldEqual, 2)
+
+				So(series[0].Points[0][0].Float64, ShouldEqual, 1)
+				So(series[0].Points[0][1].Float64, ShouldEqual, int64(1568336523000))
+
+				So(series[0].Points[1][0].Float64, ShouldEqual, 3)
+				So(series[0].Points[1][1].Float64, ShouldEqual, int64(1568426523000))
+
+				So(series[1].Name, ShouldEqual, "{segment=b}.value")
+				So(series[1].Points[0][0].Float64, ShouldEqual, 2)
+				So(series[1].Points[0][1].Float64, ShouldEqual, int64(1568336523000))
+
+				So(series[1].Points[1][0].Float64, ShouldEqual, 4)
+				So(series[1].Points[1][1].Float64, ShouldEqual, int64(1568426523000))
+
+				Convey("with alias", func() {
+					data, err := ioutil.ReadFile("./test-data/applicationinsights/2-application-insights-response-raw-query-segmented.json")
+					So(err, ShouldBeNil)
+
+					query := &ApplicationInsightsQuery{
+						IsRaw:             true,
+						TimeColumnName:    "timestamp",
+						ValueColumnName:   "value",
+						SegmentColumnName: "segment",
+						Alias:             "{{metric}} {{dimensionname}} {{dimensionvalue}}",
+					}
+					series, _, err := datasource.parseTimeSeriesFromQuery(data, query)
+					So(err, ShouldBeNil)
+
+					So(len(series), ShouldEqual, 2)
+					So(series[0].Name, ShouldEqual, "value segment a")
+					So(series[1].Name, ShouldEqual, "value segment b")
+
+				})
+			})
+		})
+
+		Convey("Parse Application Insights metrics API", func() {
+			Convey("single value", func() {
+				data, err := ioutil.ReadFile("./test-data/applicationinsights/3-application-insights-response-metrics-single-value.json")
+				So(err, ShouldBeNil)
+				query := &ApplicationInsightsQuery{
+					IsRaw: false,
+				}
+				series, err := datasource.parseTimeSeriesFromMetrics(data, query)
+				So(err, ShouldBeNil)
+
+				So(len(series), ShouldEqual, 1)
+				So(series[0].Name, ShouldEqual, "value")
+				So(len(series[0].Points), ShouldEqual, 1)
+
+				So(series[0].Points[0][0].Float64, ShouldEqual, 1.2)
+				So(series[0].Points[0][1].Float64, ShouldEqual, int64(1568340123000))
+			})
+
+			Convey("1H separation", func() {
+				data, err := ioutil.ReadFile("./test-data/applicationinsights/4-application-insights-response-metrics-no-segment.json")
+				So(err, ShouldBeNil)
+				query := &ApplicationInsightsQuery{
+					IsRaw: false,
+				}
+				series, err := datasource.parseTimeSeriesFromMetrics(data, query)
+				So(err, ShouldBeNil)
+
+				So(len(series), ShouldEqual, 1)
+				So(series[0].Name, ShouldEqual, "value")
+				So(len(series[0].Points), ShouldEqual, 2)
+
+				So(series[0].Points[0][0].Float64, ShouldEqual, 1)
+				So(series[0].Points[0][1].Float64, ShouldEqual, int64(1568340123000))
+				So(series[0].Points[1][0].Float64, ShouldEqual, 2)
+				So(series[0].Points[1][1].Float64, ShouldEqual, int64(1568343723000))
+
+				Convey("with segmentation", func() {
+					data, err := ioutil.ReadFile("./test-data/applicationinsights/4-application-insights-response-metrics-segmented.json")
+					So(err, ShouldBeNil)
+					query := &ApplicationInsightsQuery{
+						IsRaw: false,
+					}
+					series, err := datasource.parseTimeSeriesFromMetrics(data, query)
+					So(err, ShouldBeNil)
+
+					So(len(series), ShouldEqual, 2)
+					So(series[0].Name, ShouldEqual, "{blob=a}.value")
+					So(len(series[0].Points), ShouldEqual, 2)
+
+					So(series[0].Points[0][0].Float64, ShouldEqual, 1)
+					So(series[0].Points[0][1].Float64, ShouldEqual, int64(1568340123000))
+					So(series[0].Points[1][0].Float64, ShouldEqual, 2)
+					So(series[0].Points[1][1].Float64, ShouldEqual, int64(1568343723000))
+
+					So(series[1].Name, ShouldEqual, "{blob=b}.value")
+					So(len(series[1].Points), ShouldEqual, 2)
+
+					So(series[1].Points[0][0].Float64, ShouldEqual, 3)
+					So(series[1].Points[0][1].Float64, ShouldEqual, int64(1568340123000))
+					So(series[1].Points[1][0].Float64, ShouldEqual, 4)
+					So(series[1].Points[1][1].Float64, ShouldEqual, int64(1568343723000))
+
+					Convey("with alias", func() {
+						data, err := ioutil.ReadFile("./test-data/applicationinsights/4-application-insights-response-metrics-segmented.json")
+						So(err, ShouldBeNil)
+						query := &ApplicationInsightsQuery{
+							IsRaw: false,
+							Alias: "{{metric}} {{dimensionname}} {{dimensionvalue}}",
+						}
+						series, err := datasource.parseTimeSeriesFromMetrics(data, query)
+						So(err, ShouldBeNil)
+
+						So(len(series), ShouldEqual, 2)
+						So(series[0].Name, ShouldEqual, "value blob a")
+						So(series[1].Name, ShouldEqual, "value blob b")
+					})
+				})
+			})
+		})
+	})
+}

pkg/tsdb/azuremonitor/azuremonitor-datasource.go

@@ -107,7 +107,7 @@ func (e *AzureMonitorDatasource) buildQueries(queries []*tsdb.Query, timeRange *
 		timeGrain := fmt.Sprintf("%v", azureMonitorTarget["timeGrain"])
 		timeGrains := azureMonitorTarget["allowedTimeGrainsMs"]
 		if timeGrain == "auto" {
-			timeGrain, err = e.setAutoTimeGrain(query.IntervalMs, timeGrains)
+			timeGrain, err = setAutoTimeGrain(query.IntervalMs, timeGrains)
 			if err != nil {
 				return nil, err
 			}
@@ -147,35 +147,6 @@ func (e *AzureMonitorDatasource) buildQueries(queries []*tsdb.Query, timeRange *
 	return azureMonitorQueries, nil
 }
 
-// setAutoTimeGrain tries to find the closest interval to the query's intervalMs value
-// if the metric has a limited set of possible intervals/time grains then use those
-// instead of the default list of intervals
-func (e *AzureMonitorDatasource) setAutoTimeGrain(intervalMs int64, timeGrains interface{}) (string, error) {
-	// parses array of numbers from the timeGrains json field
-	allowedTimeGrains := []int64{}
-	tgs, ok := timeGrains.([]interface{})
-	if ok {
-		for _, v := range tgs {
-			jsonNumber, ok := v.(json.Number)
-			if ok {
-				tg, err := jsonNumber.Int64()
-				if err == nil {
-					allowedTimeGrains = append(allowedTimeGrains, tg)
-				}
-			}
-		}
-	}
-
-	autoInterval := e.findClosestAllowedIntervalMS(intervalMs, allowedTimeGrains)
-	tg := &TimeGrain{}
-	autoTimeGrain, err := tg.createISO8601DurationFromIntervalMS(autoInterval)
-	if err != nil {
-		return "", err
-	}
-
-	return autoTimeGrain, nil
-}
-
 func (e *AzureMonitorDatasource) executeQuery(ctx context.Context, query *AzureMonitorQuery, queries []*tsdb.Query, timeRange *tsdb.TimeRange) (*tsdb.QueryResult, AzureMonitorResponse, error) {
 	queryResult := &tsdb.QueryResult{Meta: simplejson.New(), RefId: query.RefID}
 
@@ -203,7 +174,7 @@ func (e *AzureMonitorDatasource) executeQuery(ctx context.Context, query *AzureM
 		opentracing.HTTPHeaders,
 		opentracing.HTTPHeadersCarrier(req.Header))
 
-	azlog.Debug("AzureMonitor", "Request URL", req.URL.String())
+	azlog.Debug("AzureMonitor", "Request ApiURL", req.URL.String())
 	res, err := ctxhttp.Do(ctx, e.httpClient, req)
 	if err != nil {
 		queryResult.Error = err
@@ -290,7 +261,7 @@ func (e *AzureMonitorDatasource) parseResponse(queryRes *tsdb.QueryResult, data
 			metadataName = series.Metadatavalues[0].Name.LocalizedValue
 			metadataValue = series.Metadatavalues[0].Value
 		}
-		metricName := formatLegendKey(query.Alias, query.UrlComponents["resourceName"], data.Value[0].Name.LocalizedValue, metadataName, metadataValue, data.Namespace, data.Value[0].ID)
+		metricName := formatAzureMonitorLegendKey(query.Alias, query.UrlComponents["resourceName"], data.Value[0].Name.LocalizedValue, metadataName, metadataValue, data.Namespace, data.Value[0].ID)
 
 		for _, point := range series.Data {
 			var value float64
@@ -321,35 +292,9 @@ func (e *AzureMonitorDatasource) parseResponse(queryRes *tsdb.QueryResult, data
 	return nil
 }
 
-// findClosestAllowedIntervalMs is used for the auto time grain setting.
+// formatAzureMonitorLegendKey builds the legend key or timeseries name
-// It finds the closest time grain from the list of allowed time grains for Azure Monitor
-// using the Grafana interval in milliseconds
-// Some metrics only allow a limited list of time grains. The allowedTimeGrains parameter
-// allows overriding the default list of allowed time grains.
-func (e *AzureMonitorDatasource) findClosestAllowedIntervalMS(intervalMs int64, allowedTimeGrains []int64) int64 {
-	allowedIntervals := defaultAllowedIntervalsMS
-
-	if len(allowedTimeGrains) > 0 {
-		allowedIntervals = allowedTimeGrains
-	}
-
-	closest := allowedIntervals[0]
-
-	for i, allowed := range allowedIntervals {
-		if intervalMs > allowed {
-			if i+1 < len(allowedIntervals) {
-				closest = allowedIntervals[i+1]
-			} else {
-				closest = allowed
-			}
-		}
-	}
-	return closest
-}
-
-// formatLegendKey builds the legend key or timeseries name
 // Alias patterns like {{resourcename}} are replaced with the appropriate data values.
-func formatLegendKey(alias string, resourceName string, metricName string, metadataName string, metadataValue string, namespace string, seriesID string) string {
+func formatAzureMonitorLegendKey(alias string, resourceName string, metricName string, metadataName string, metadataValue string, namespace string, seriesID string) string {
 	if alias == "" {
 		if len(metadataName) > 0 {
 			return fmt.Sprintf("%s{%s=%s}.%s", resourceName, metadataName, metadataValue, metricName)

pkg/tsdb/azuremonitor/azuremonitor-datasource_test.go

@@ -167,7 +167,7 @@ func TestAzureMonitorDatasource(t *testing.T) {
 
 		Convey("Parse AzureMonitor API response in the time series format", func() {
 			Convey("when data from query aggregated as average to one time series", func() {
-				data, err := loadTestFile("./test-data/1-azure-monitor-response-avg.json")
+				data, err := loadTestFile("./test-data/azuremonitor/1-azure-monitor-response-avg.json")
 				So(err, ShouldBeNil)
 				So(data.Interval, ShouldEqual, "PT1M")
 
@@ -204,7 +204,7 @@ func TestAzureMonitorDatasource(t *testing.T) {
 			})
 
 			Convey("when data from query aggregated as total to one time series", func() {
-				data, err := loadTestFile("./test-data/2-azure-monitor-response-total.json")
+				data, err := loadTestFile("./test-data/azuremonitor/2-azure-monitor-response-total.json")
 				So(err, ShouldBeNil)
 
 				res := &tsdb.QueryResult{Meta: simplejson.New(), RefId: "A"}
@@ -224,7 +224,7 @@ func TestAzureMonitorDatasource(t *testing.T) {
 			})
 
 			Convey("when data from query aggregated as maximum to one time series", func() {
-				data, err := loadTestFile("./test-data/3-azure-monitor-response-maximum.json")
+				data, err := loadTestFile("./test-data/azuremonitor/3-azure-monitor-response-maximum.json")
 				So(err, ShouldBeNil)
 
 				res := &tsdb.QueryResult{Meta: simplejson.New(), RefId: "A"}
@@ -244,7 +244,7 @@ func TestAzureMonitorDatasource(t *testing.T) {
 			})
 
 			Convey("when data from query aggregated as minimum to one time series", func() {
-				data, err := loadTestFile("./test-data/4-azure-monitor-response-minimum.json")
+				data, err := loadTestFile("./test-data/azuremonitor/4-azure-monitor-response-minimum.json")
 				So(err, ShouldBeNil)
 
 				res := &tsdb.QueryResult{Meta: simplejson.New(), RefId: "A"}
@@ -264,7 +264,7 @@ func TestAzureMonitorDatasource(t *testing.T) {
 			})
 
 			Convey("when data from query aggregated as Count to one time series", func() {
-				data, err := loadTestFile("./test-data/5-azure-monitor-response-count.json")
+				data, err := loadTestFile("./test-data/azuremonitor/5-azure-monitor-response-count.json")
 				So(err, ShouldBeNil)
 
 				res := &tsdb.QueryResult{Meta: simplejson.New(), RefId: "A"}
@@ -284,7 +284,7 @@ func TestAzureMonitorDatasource(t *testing.T) {
 			})
 
 			Convey("when data from query aggregated as total and has dimension filter", func() {
-				data, err := loadTestFile("./test-data/6-azure-monitor-response-multi-dimension.json")
+				data, err := loadTestFile("./test-data/azuremonitor/6-azure-monitor-response-multi-dimension.json")
 				So(err, ShouldBeNil)
 
 				res := &tsdb.QueryResult{Meta: simplejson.New(), RefId: "A"}
@@ -311,7 +311,7 @@ func TestAzureMonitorDatasource(t *testing.T) {
 			})
 
 			Convey("when data from query has alias patterns", func() {
-				data, err := loadTestFile("./test-data/2-azure-monitor-response-total.json")
+				data, err := loadTestFile("./test-data/azuremonitor/2-azure-monitor-response-total.json")
 				So(err, ShouldBeNil)
 
 				res := &tsdb.QueryResult{Meta: simplejson.New(), RefId: "A"}
@@ -331,7 +331,7 @@ func TestAzureMonitorDatasource(t *testing.T) {
 			})
 
 			Convey("when data has dimension filters and alias patterns", func() {
-				data, err := loadTestFile("./test-data/6-azure-monitor-response-multi-dimension.json")
+				data, err := loadTestFile("./test-data/azuremonitor/6-azure-monitor-response-multi-dimension.json")
 				So(err, ShouldBeNil)
 
 				res := &tsdb.QueryResult{Meta: simplejson.New(), RefId: "A"}
@@ -363,16 +363,16 @@ func TestAzureMonitorDatasource(t *testing.T) {
 				"2d":  172800000,
 			}
 
-			closest := datasource.findClosestAllowedIntervalMS(intervals["3m"], []int64{})
+			closest := findClosestAllowedIntervalMS(intervals["3m"], []int64{})
 			So(closest, ShouldEqual, intervals["5m"])
 
-			closest = datasource.findClosestAllowedIntervalMS(intervals["10m"], []int64{})
+			closest = findClosestAllowedIntervalMS(intervals["10m"], []int64{})
 			So(closest, ShouldEqual, intervals["15m"])
 
-			closest = datasource.findClosestAllowedIntervalMS(intervals["2d"], []int64{})
+			closest = findClosestAllowedIntervalMS(intervals["2d"], []int64{})
 			So(closest, ShouldEqual, intervals["1d"])
 
-			closest = datasource.findClosestAllowedIntervalMS(intervals["3m"], []int64{intervals["1d"]})
+			closest = findClosestAllowedIntervalMS(intervals["3m"], []int64{intervals["1d"]})
 			So(closest, ShouldEqual, intervals["1d"])
 		})
 	})

pkg/tsdb/azuremonitor/azuremonitor-time.go

@@ -0,0 +1,58 @@
+package azuremonitor
+
+import "encoding/json"
+
+// setAutoTimeGrain tries to find the closest interval to the query's intervalMs value
+// if the metric has a limited set of possible intervals/time grains then use those
+// instead of the default list of intervals
+func setAutoTimeGrain(intervalMs int64, timeGrains interface{}) (string, error) {
+	// parses array of numbers from the timeGrains json field
+	allowedTimeGrains := []int64{}
+	tgs, ok := timeGrains.([]interface{})
+	if ok {
+		for _, v := range tgs {
+			jsonNumber, ok := v.(json.Number)
+			if ok {
+				tg, err := jsonNumber.Int64()
+				if err == nil {
+					allowedTimeGrains = append(allowedTimeGrains, tg)
+				}
+			}
+		}
+	}
+
+	autoInterval := findClosestAllowedIntervalMS(intervalMs, allowedTimeGrains)
+	tg := &TimeGrain{}
+	autoTimeGrain, err := tg.createISO8601DurationFromIntervalMS(autoInterval)
+	if err != nil {
+		return "", err
+	}
+
+	return autoTimeGrain, nil
+}
+
+// findClosestAllowedIntervalMs is used for the auto time grain setting.
+// It finds the closest time grain from the list of allowed time grains for Azure Monitor
+// using the Grafana interval in milliseconds
+// Some metrics only allow a limited list of time grains. The allowedTimeGrains parameter
+// allows overriding the default list of allowed time grains.
+func findClosestAllowedIntervalMS(intervalMs int64, allowedTimeGrains []int64) int64 {
+	allowedIntervals := defaultAllowedIntervalsMS
+
+	if len(allowedTimeGrains) > 0 {
+		allowedIntervals = allowedTimeGrains
+	}
+
+	closest := allowedIntervals[0]
+
+	for i, allowed := range allowedIntervals {
+		if intervalMs > allowed {
+			if i+1 < len(allowedIntervals) {
+				closest = allowedIntervals[i+1]
+			} else {
+				closest = allowed
+			}
+		}
+	}
+	return closest
+}

pkg/tsdb/azuremonitor/azuremonitor.go

@@ -46,10 +46,10 @@ func init() {
 // executes the queries against the API and parses the response into
 // the right format
 func (e *AzureMonitorExecutor) Query(ctx context.Context, dsInfo *models.DataSource, tsdbQuery *tsdb.TsdbQuery) (*tsdb.Response, error) {
-	var result *tsdb.Response
 	var err error
 
 	var azureMonitorQueries []*tsdb.Query
+	var applicationInsightsQueries []*tsdb.Query
 
 	for _, query := range tsdbQuery.Queries {
 		queryType := query.Model.Get("queryType").MustString("")
@@ -57,6 +57,8 @@ func (e *AzureMonitorExecutor) Query(ctx context.Context, dsInfo *models.DataSou
 		switch queryType {
 		case "Azure Monitor":
 			azureMonitorQueries = append(azureMonitorQueries, query)
+		case "Application Insights":
+			applicationInsightsQueries = append(applicationInsightsQueries, query)
 		default:
 			return nil, fmt.Errorf("Alerting not supported for %s", queryType)
 		}
@@ -67,7 +69,24 @@ func (e *AzureMonitorExecutor) Query(ctx context.Context, dsInfo *models.DataSou
 		dsInfo:     e.dsInfo,
 	}
 
-	result, err = azDatasource.executeTimeSeriesQuery(ctx, azureMonitorQueries, tsdbQuery.TimeRange)
+	aiDatasource := &ApplicationInsightsDatasource{
+		httpClient: e.httpClient,
+		dsInfo:     e.dsInfo,
+	}
 
-	return result, err
+	azResult, err := azDatasource.executeTimeSeriesQuery(ctx, azureMonitorQueries, tsdbQuery.TimeRange)
+	if err != nil {
+		return nil, err
+	}
+
+	aiResult, err := aiDatasource.executeTimeSeriesQuery(ctx, applicationInsightsQueries, tsdbQuery.TimeRange)
+	if err != nil {
+		return nil, err
+	}
+
+	for k, v := range aiResult.Results {
+		azResult.Results[k] = v
+	}
+
+	return azResult, nil
 }

pkg/tsdb/azuremonitor/macros.go

@@ -0,0 +1,118 @@
+package azuremonitor
+
+import (
+	"fmt"
+	"regexp"
+	"strings"
+	"time"
+
+	"github.com/grafana/grafana/pkg/tsdb"
+)
+
+const rsIdentifier = `([_a-zA-Z0-9]+)`
+const sExpr = `\$` + rsIdentifier + `(?:\(([^\)]*)\))?`
+
+type kqlMacroEngine struct {
+	timeRange *tsdb.TimeRange
+	query     *tsdb.Query
+}
+
+func KqlInterpolate(query *tsdb.Query, timeRange *tsdb.TimeRange, kql string) (string, error) {
+	engine := kqlMacroEngine{}
+	return engine.Interpolate(query, timeRange, kql)
+}
+
+func (m *kqlMacroEngine) Interpolate(query *tsdb.Query, timeRange *tsdb.TimeRange, kql string) (string, error) {
+	m.timeRange = timeRange
+	m.query = query
+	rExp, _ := regexp.Compile(sExpr)
+	var macroError error
+
+	kql = m.ReplaceAllStringSubmatchFunc(rExp, kql, func(groups []string) string {
+		args := []string{}
+		if len(groups) > 2 {
+			args = strings.Split(groups[2], ",")
+		}
+
+		for i, arg := range args {
+			args[i] = strings.Trim(arg, " ")
+		}
+		res, err := m.evaluateMacro(groups[1], args)
+		if err != nil && macroError == nil {
+			macroError = err
+			return "macro_error()"
+		}
+		return res
+	})
+
+	if macroError != nil {
+		return "", macroError
+	}
+
+	return kql, nil
+}
+
+func (m *kqlMacroEngine) evaluateMacro(name string, args []string) (string, error) {
+	switch name {
+	case "__timeFilter":
+		timeColumn := "timestamp"
+		if len(args) > 0 && args[0] != "" {
+			timeColumn = args[0]
+		}
+		return fmt.Sprintf("['%s'] >= datetime('%s') and ['%s'] <= datetime('%s')", timeColumn, m.timeRange.GetFromAsTimeUTC().Format(time.RFC3339), timeColumn, m.timeRange.GetToAsTimeUTC().Format(time.RFC3339)), nil
+	case "__from":
+		return fmt.Sprintf("datetime('%s')", m.timeRange.GetFromAsTimeUTC().Format(time.RFC3339)), nil
+	case "__to":
+		return fmt.Sprintf("datetime('%s')", m.timeRange.GetToAsTimeUTC().Format(time.RFC3339)), nil
+	case "__interval":
+		var interval time.Duration
+		if m.query.IntervalMs == 0 {
+			to := m.timeRange.MustGetTo().UnixNano()
+			from := m.timeRange.MustGetFrom().UnixNano()
+			// default to "100 datapoints" if nothing in the query is more specific
+			defaultInterval := time.Duration((to - from) / 60)
+			var err error
+			interval, err = tsdb.GetIntervalFrom(m.query.DataSource, m.query.Model, defaultInterval)
+			if err != nil {
+				azlog.Warn("Unable to get interval from query", "datasource", m.query.DataSource, "model", m.query.Model)
+				interval = defaultInterval
+			}
+		} else {
+			interval = time.Millisecond * time.Duration(m.query.IntervalMs)
+		}
+		return fmt.Sprintf("%dms", int(interval/time.Millisecond)), nil
+	case "__contains":
+		if len(args) < 2 || args[0] == "" || args[1] == "" {
+			return "", fmt.Errorf("macro %v needs colName and variableSet", name)
+		}
+
+		if args[1] == "all" {
+			return "1 == 1", nil
+		}
+
+		return fmt.Sprintf("['%s'] in ('%s')", args[0], args[1]), nil
+	default:
+		return "", fmt.Errorf("Unknown macro %v", name)
+	}
+}
+
+func (m *kqlMacroEngine) ReplaceAllStringSubmatchFunc(re *regexp.Regexp, str string, repl func([]string) string) string {
+	result := ""
+	lastIndex := 0
+
+	for _, v := range re.FindAllSubmatchIndex([]byte(str), -1) {
+		groups := []string{}
+		for i := 0; i < len(v); i += 2 {
+			if v[i] < 0 {
+				groups = append(groups, "")
+			} else {
+				groups = append(groups, str[v[i]:v[i+1]])
+			}
+		}
+
+		result += str[lastIndex:v[0]] + repl(groups)
+		lastIndex = v[1]
+	}
+
+	return result + str[lastIndex:]
+}

pkg/tsdb/azuremonitor/test-data/applicationinsights/1-application-insights-response-raw-query.json

@@ -0,0 +1,27 @@
+{
+  "tables": [
+    {
+      "name": "PrimaryResult",
+      "columns": [
+        {
+          "name": "timestamp",
+          "type": "datetime"
+        },
+        {
+          "name": "value",
+          "type": "int"
+        }
+      ],
+      "rows": [
+        [
+          "2019-09-13T01:02:03.456789Z",
+          1
+        ],
+        [
+          "2019-09-13T02:02:03.456789Z",
+          2
+        ]
+      ]
+    }
+  ]
+}

pkg/tsdb/azuremonitor/test-data/applicationinsights/2-application-insights-response-raw-query-segmented.json

@@ -0,0 +1,43 @@
+{
+  "tables": [
+    {
+      "name": "PrimaryResult",
+      "columns": [
+        {
+          "name": "timestamp",
+          "type": "datetime"
+        },
+        {
+          "name": "value",
+          "type": "int"
+        },
+        {
+          "name": "segment",
+          "type": "string"
+        }
+      ],
+      "rows": [
+        [
+          "2019-09-13T01:02:03.456789Z",
+          1,
+          "a"
+        ],
+        [
+          "2019-09-13T01:02:03.456789Z",
+          2,
+          "b"
+        ],
+        [
+          "2019-09-14T02:02:03.456789Z",
+          3,
+          "a"
+        ],
+        [
+          "2019-09-14T02:02:03.456789Z",
+          4,
+          "b"
+        ]
+      ]
+    }
+  ]
+}

pkg/tsdb/azuremonitor/test-data/applicationinsights/3-application-insights-response-metrics-single-value.json

@@ -0,0 +1,9 @@
+{
+  "value": {
+    "start": "2019-09-13T01:02:03.456789Z",
+    "end": "2019-09-13T02:02:03.456789Z",
+    "value": {
+      "avg": 1.2
+    }
+  }
+}

pkg/tsdb/azuremonitor/test-data/applicationinsights/4-application-insights-response-metrics-no-segment.json

@@ -0,0 +1,23 @@
+{
+  "value": {
+    "start": "2019-09-13T01:02:03.456789Z",
+    "end": "2019-09-13T03:02:03.456789Z",
+    "interval": "PT1H",
+    "segments": [
+      {
+        "start": "2019-09-13T01:02:03.456789Z",
+        "end": "2019-09-13T02:02:03.456789Z",
+        "value": {
+          "avg": 1
+        }
+      },
+      {
+        "start": "2019-09-13T02:02:03.456789Z",
+        "end": "2019-09-13T03:02:03.456789Z",
+        "value": {
+          "avg": 2
+        }
+      }
+    ]
+  }
+}

pkg/tsdb/azuremonitor/test-data/applicationinsights/4-application-insights-response-metrics-segmented.json

@@ -0,0 +1,45 @@
+{
+  "value": {
+    "start": "2019-09-13T01:02:03.456789Z",
+    "end": "2019-09-13T03:02:03.456789Z",
+    "interval": "PT1H",
+    "segments": [
+      {
+        "start": "2019-09-13T01:02:03.456789Z",
+        "end": "2019-09-13T02:02:03.456789Z",
+        "segments": [
+          {
+            "value": {
+              "avg": 1
+            },
+            "blob": "a"
+          },
+          {
+            "value": {
+              "avg": 3
+            },
+            "blob": "b"
+          }
+        ]
+      },
+      {
+        "start": "2019-09-13T02:02:03.456789Z",
+        "end": "2019-09-13T03:02:03.456789Z",
+        "segments": [
+          {
+            "value": {
+              "avg": 2
+            },
+            "blob": "a"
+          },
+          {
+            "value": {
+              "avg": 4
+            },
+            "blob": "b"
+          }
+        ]
+      }
+    ]
+  }
+}

pkg/tsdb/azuremonitor/types.go

@@ -51,17 +51,32 @@ type AzureMonitorResponse struct {
 	Resourceregion string `json:"resourceregion"`
 }
 
-// ApplicationInsightsResponse is the json response from the Application Insights API
 type ApplicationInsightsResponse struct {
+	MetricResponse *ApplicationInsightsMetricsResponse
+	QueryResponse  *ApplicationInsightsQueryResponse
+}
+
+// ApplicationInsightsResponse is the json response from the Application Insights API
+type ApplicationInsightsQueryResponse struct {
 	Tables []struct {
-		TableName string `json:"TableName"`
+		Name    string `json:"name"`
-		Columns   []struct {
+		Columns []struct {
-			ColumnName string `json:"ColumnName"`
+			Name string `json:"name"`
-			DataType   string `json:"DataType"`
+			Type string `json:"type"`
-			ColumnType string `json:"ColumnType"`
+		} `json:"columns"`
-		} `json:"Columns"`
+		Rows [][]interface{} `json:"rows"`
-		Rows [][]interface{} `json:"Rows"`
+	} `json:"tables"`
-	} `json:"Tables"`
+}
+
+// ApplicationInsightsMetricsResponse is the json response from the Application Insights API
+type ApplicationInsightsMetricsResponse struct {
+	Name     string
+	Segments []struct {
+		Start     time.Time
+		End       time.Time
+		Segmented map[string]float64
+		Value     float64
+	}
 }
 
 // AzureLogAnalyticsResponse is the json response object from the Azure Log Analytics API.

pkg/util/url.go

@@ -5,7 +5,7 @@ import (
 	"strings"
 )
 
-// URLQueryReader is a URL query type.
+// URLQueryReader is a ApiURL query type.
 type URLQueryReader struct {
 	values url.Values
 }
@@ -22,7 +22,7 @@ func NewURLQueryReader(urlInfo *url.URL) (*URLQueryReader, error) {
 	}, nil
 }
 
-// Get parse parameters from an URL. If the parameter does not exist, it returns
+// Get parse parameters from an ApiURL. If the parameter does not exist, it returns
 // the default value.
 func (r *URLQueryReader) Get(name string, def string) string {
 	val := r.values[name]
@@ -33,7 +33,7 @@ func (r *URLQueryReader) Get(name string, def string) string {
 	return val[0]
 }
 
-// JoinURLFragments joins two URL fragments into only one URL string.
+// JoinURLFragments joins two ApiURL fragments into only one ApiURL string.
 func JoinURLFragments(a, b string) string {
 	aslash := strings.HasSuffix(a, "/")
 	bslash := strings.HasPrefix(b, "/")

public/app/plugins/datasource/grafana-azure-monitor-datasource/app_insights/app_insights_datasource.test.ts

@@ -1,8 +1,8 @@
-import AzureMonitorDatasource from '../datasource';
+import Datasource from '../datasource';
+import { DataFrame, toUtc } from '@grafana/data';
+import { TemplateSrv } from 'app/features/templating/template_srv';
 // @ts-ignore
 import Q from 'q';
-import { TemplateSrv } from 'app/features/templating/template_srv';
-import { toUtc } from '@grafana/data';
 
 describe('AppInsightsDatasource', () => {
   const ctx: any = {
@@ -17,7 +17,7 @@ describe('AppInsightsDatasource', () => {
       url: 'http://appinsightsapi',
     };
 
-    ctx.ds = new AzureMonitorDatasource(ctx.instanceSettings, ctx.backendSrv, ctx.templateSrv, ctx.$q);
+    ctx.ds = new Datasource(ctx.instanceSettings, ctx.backendSrv, ctx.templateSrv, ctx.$q);
   });
 
   describe('When performing testDatasource', () => {
@@ -108,7 +108,121 @@ describe('AppInsightsDatasource', () => {
     });
   });
 
-  describe('When performing query', () => {
+  describe('When performing raw query', () => {
+    const queryString =
+      'metrics ' +
+      '| where $__timeFilter(timestamp) ' +
+      '| where name == "testMetrics" ' +
+      '| summarize max=max(valueMax) by bin(timestamp, $__interval), partition';
+
+    const options = {
+      range: {
+        from: toUtc('2017-08-22T20:00:00Z'),
+        to: toUtc('2017-08-22T23:59:00Z'),
+      },
+      targets: [
+        {
+          apiVersion: '2016-09-01',
+          refId: 'A',
+          queryType: 'Application Insights',
+          appInsights: {
+            rawQuery: true,
+            rawQueryString: queryString,
+            timeColumn: 'timestamp',
+            valueColumn: 'max',
+            segmentColumn: undefined as string,
+          },
+        },
+      ],
+    };
+
+    describe('with no grouping', () => {
+      const response: any = {
+        results: {
+          A: {
+            refId: 'A',
+            meta: {},
+            series: [
+              {
+                name: 'PrimaryResult',
+                points: [[2.2075, 1558278660000]],
+              },
+            ],
+            tables: null,
+          },
+        },
+      };
+
+      beforeEach(() => {
+        ctx.backendSrv.datasourceRequest = (options: any) => {
+          expect(options.url).toContain('/api/tsdb/query');
+          expect(options.data.queries.length).toBe(1);
+          expect(options.data.queries[0].refId).toBe('A');
+          expect(options.data.queries[0].appInsights.rawQueryString).toEqual(queryString);
+          expect(options.data.queries[0].appInsights.timeColumn).toEqual('timestamp');
+          expect(options.data.queries[0].appInsights.valueColumn).toEqual('max');
+          expect(options.data.queries[0].appInsights.segmentColumn).toBeUndefined();
+          return ctx.$q.when({ data: response, status: 200 });
+        };
+      });
+
+      it('should return a list of datapoints', () => {
+        return ctx.ds.query(options).then((results: any) => {
+          expect(results.data.length).toBe(1);
+          const data = results.data[0] as DataFrame;
+          expect(data.name).toEqual('PrimaryResult');
+          expect(data.fields[0].values.length).toEqual(1);
+          expect(data.fields[1].values.get(0)).toEqual(1558278660000);
+          expect(data.fields[0].values.get(0)).toEqual(2.2075);
+        });
+      });
+    });
+
+    describe('with grouping', () => {
+      const response: any = {
+        results: {
+          A: {
+            refId: 'A',
+            meta: {},
+            series: [
+              {
+                name: 'paritionA',
+                points: [[2.2075, 1558278660000]],
+              },
+            ],
+            tables: null,
+          },
+        },
+      };
+
+      beforeEach(() => {
+        options.targets[0].appInsights.segmentColumn = 'partition';
+        ctx.backendSrv.datasourceRequest = (options: any) => {
+          expect(options.url).toContain('/api/tsdb/query');
+          expect(options.data.queries.length).toBe(1);
+          expect(options.data.queries[0].refId).toBe('A');
+          expect(options.data.queries[0].appInsights.rawQueryString).toEqual(queryString);
+          expect(options.data.queries[0].appInsights.timeColumn).toEqual('timestamp');
+          expect(options.data.queries[0].appInsights.valueColumn).toEqual('max');
+          expect(options.data.queries[0].appInsights.segmentColumn).toEqual('partition');
+          return ctx.$q.when({ data: response, status: 200 });
+        };
+      });
+
+      it('should return a list of datapoints', () => {
+        return ctx.ds.query(options).then((results: any) => {
+          expect(results.data.length).toBe(1);
+          const data = results.data[0] as DataFrame;
+          expect(data.name).toEqual('paritionA');
+          expect(data.fields[0].values.length).toEqual(1);
+          expect(data.fields[1].values.get(0)).toEqual(1558278660000);
+          expect(data.fields[0].values.get(0)).toEqual(2.2075);
+        });
+      });
+    });
+  });
+
+  describe('When performing metric query', () => {
     const options = {
       range: {
         from: toUtc('2017-08-22T20:00:00Z'),
@@ -121,30 +235,37 @@ describe('AppInsightsDatasource', () => {
           queryType: 'Application Insights',
           appInsights: {
             metricName: 'exceptions/server',
-            groupBy: '',
+            dimension: '',
-            timeGrainType: 'none',
+            timeGrain: 'none',
-            timeGrain: '',
-            timeGrainUnit: '',
-            alias: '',
           },
         },
       ],
     };
 
     describe('and with a single value', () => {
-      const response = {
+      const response: any = {
-        value: {
+        results: {
-          start: '2017-08-30T15:53:58.845Z',
+          A: {
-          end: '2017-09-06T15:53:58.845Z',
+            refId: 'A',
-          'exceptions/server': {
+            meta: {},
-            sum: 100,
+            series: [
+              {
+                name: 'exceptions/server',
+                points: [[2.2075, 1558278660000]],
+              },
+            ],
+            tables: null,
           },
         },
       };
 
       beforeEach(() => {
-        ctx.backendSrv.datasourceRequest = (options: { url: string }) => {
+        ctx.backendSrv.datasourceRequest = (options: any) => {
-          expect(options.url).toContain('/metrics/exceptions/server');
+          expect(options.url).toContain('/api/tsdb/query');
+          expect(options.data.queries.length).toBe(1);
+          expect(options.data.queries[0].refId).toBe('A');
+          expect(options.data.queries[0].appInsights.rawQueryString).toBeUndefined();
+          expect(options.data.queries[0].appInsights.metricName).toBe('exceptions/server');
           return ctx.$q.when({ data: response, status: 200 });
         };
       });
@@ -152,46 +273,39 @@ describe('AppInsightsDatasource', () => {
       it('should return a single datapoint', () => {
         return ctx.ds.query(options).then((results: any) => {
           expect(results.data.length).toBe(1);
-          expect(results.data[0].datapoints.length).toBe(1);
+          const data = results.data[0] as DataFrame;
-          expect(results.data[0].target).toEqual('exceptions/server');
+          expect(data.name).toEqual('exceptions/server');
-          expect(results.data[0].datapoints[0][1]).toEqual(1504713238845);
+          expect(data.fields[1].values.get(0)).toEqual(1558278660000);
-          expect(results.data[0].datapoints[0][0]).toEqual(100);
+          expect(data.fields[0].values.get(0)).toEqual(2.2075);
         });
       });
     });
 
     describe('and with an interval group and without a segment group by', () => {
-      const response = {
+      const response: any = {
-        value: {
+        results: {
-          start: '2017-08-30T15:53:58.845Z',
+          A: {
-          end: '2017-09-06T15:53:58.845Z',
+            refId: 'A',
-          interval: 'PT1H',
+            meta: {},
-          segments: [
+            series: [
-            {
+              {
-              start: '2017-08-30T15:53:58.845Z',
+                name: 'exceptions/server',
-              end: '2017-08-30T16:00:00.000Z',
+                points: [[3, 1504108800000], [6, 1504112400000]],
-              'exceptions/server': {
-                sum: 3,
               },
-            },
+            ],
-            {
+            tables: null,
-              start: '2017-08-30T16:00:00.000Z',
+          },
-              end: '2017-08-30T17:00:00.000Z',
-              'exceptions/server': {
-                sum: 66,
-              },
-            },
-          ],
         },
       };
 
       beforeEach(() => {
-        options.targets[0].appInsights.timeGrainType = 'specific';
+        options.targets[0].appInsights.timeGrain = 'PT30M';
-        options.targets[0].appInsights.timeGrain = '30';
+        ctx.backendSrv.datasourceRequest = (options: any) => {
-        options.targets[0].appInsights.timeGrainUnit = 'minute';
+          expect(options.url).toContain('/api/tsdb/query');
-        ctx.backendSrv.datasourceRequest = (options: { url: string }) => {
+          expect(options.data.queries[0].refId).toBe('A');
-          expect(options.url).toContain('/metrics/exceptions/server');
+          expect(options.data.queries[0].appInsights.rawQueryString).toBeUndefined();
-          expect(options.url).toContain('interval=PT30M');
+          expect(options.data.queries[0].appInsights.metricName).toBe('exceptions/server');
+          expect(options.data.queries[0].appInsights.timeGrain).toBe('PT30M');
           return ctx.$q.when({ data: response, status: 200 });
         };
       });
@@ -199,108 +313,68 @@ describe('AppInsightsDatasource', () => {
       it('should return a list of datapoints', () => {
         return ctx.ds.query(options).then((results: any) => {
           expect(results.data.length).toBe(1);
-          expect(results.data[0].datapoints.length).toBe(2);
+          const data = results.data[0] as DataFrame;
-          expect(results.data[0].target).toEqual('exceptions/server');
+          expect(data.name).toEqual('exceptions/server');
-          expect(results.data[0].datapoints[0][1]).toEqual(1504108800000);
+          expect(data.fields[0].values.length).toEqual(2);
-          expect(results.data[0].datapoints[0][0]).toEqual(3);
+          expect(data.fields[1].values.get(0)).toEqual(1504108800000);
-          expect(results.data[0].datapoints[1][1]).toEqual(1504112400000);
+          expect(data.fields[0].values.get(0)).toEqual(3);
-          expect(results.data[0].datapoints[1][0]).toEqual(66);
+          expect(data.fields[1].values.get(1)).toEqual(1504112400000);
+          expect(data.fields[0].values.get(1)).toEqual(6);
         });
       });
     });
 
     describe('and with a group by', () => {
-      const response = {
+      const response: any = {
-        value: {
+        results: {
-          start: '2017-08-30T15:53:58.845Z',
+          A: {
-          end: '2017-09-06T15:53:58.845Z',
+            refId: 'A',
-          interval: 'PT1H',
+            meta: {},
-          segments: [
+            series: [
-            {
+              {
-              start: '2017-08-30T15:53:58.845Z',
+                name: 'exceptions/server{client/city="Miami"}',
-              end: '2017-08-30T16:00:00.000Z',
+                points: [[10, 1504108800000], [20, 1504112400000]],
-              segments: [
+              },
-                {
+              {
-                  'exceptions/server': {
+                name: 'exceptions/server{client/city="San Antonio"}',
-                    sum: 10,
+                points: [[1, 1504108800000], [2, 1504112400000]],
-                  },
+              },
-                  'client/city': 'Miami',
+            ],
-                },
+            tables: null,
-                {
+          },
-                  'exceptions/server': {
-                    sum: 1,
-                  },
-                  'client/city': 'San Jose',
-                },
-              ],
-            },
-            {
-              start: '2017-08-30T16:00:00.000Z',
-              end: '2017-08-30T17:00:00.000Z',
-              segments: [
-                {
-                  'exceptions/server': {
-                    sum: 20,
-                  },
-                  'client/city': 'Miami',
-                },
-                {
-                  'exceptions/server': {
-                    sum: 2,
-                  },
-                  'client/city': 'San Antonio',
-                },
-              ],
-            },
-          ],
         },
       };
 
       describe('and with no alias specified', () => {
         beforeEach(() => {
-          options.targets[0].appInsights.groupBy = 'client/city';
+          options.targets[0].appInsights.dimension = 'client/city';
 
-          ctx.backendSrv.datasourceRequest = (options: { url: string }) => {
+          ctx.backendSrv.datasourceRequest = (options: any) => {
-            expect(options.url).toContain('/metrics/exceptions/server');
+            expect(options.url).toContain('/api/tsdb/query');
-            expect(options.url).toContain('segment=client/city');
+            expect(options.data.queries[0].appInsights.rawQueryString).toBeUndefined();
+            expect(options.data.queries[0].appInsights.metricName).toBe('exceptions/server');
+            expect(options.data.queries[0].appInsights.dimension).toBe('client/city');
             return ctx.$q.when({ data: response, status: 200 });
           };
         });
 
         it('should return a list of datapoints', () => {
           return ctx.ds.query(options).then((results: any) => {
-            expect(results.data.length).toBe(3);
+            expect(results.data.length).toBe(2);
-            expect(results.data[0].datapoints.length).toBe(2);
+            let data = results.data[0] as DataFrame;
-            expect(results.data[0].target).toEqual('exceptions/server{client/city="Miami"}');
+            expect(data.name).toEqual('exceptions/server{client/city="Miami"}');
-            expect(results.data[0].datapoints[0][1]).toEqual(1504108800000);
+            expect(data.fields[0].values.length).toEqual(2);
-            expect(results.data[0].datapoints[0][0]).toEqual(10);
+            expect(data.fields[1].values.get(0)).toEqual(1504108800000);
-            expect(results.data[0].datapoints[1][1]).toEqual(1504112400000);
+            expect(data.fields[0].values.get(0)).toEqual(10);
-            expect(results.data[0].datapoints[1][0]).toEqual(20);
+            expect(data.fields[1].values.get(1)).toEqual(1504112400000);
-          });
+            expect(data.fields[0].values.get(1)).toEqual(20);
-        });
+            data = results.data[1] as DataFrame;
-      });
+            expect(data.name).toEqual('exceptions/server{client/city="San Antonio"}');
-
+            expect(data.fields[0].values.length).toEqual(2);
-      describe('and with an alias specified', () => {
+            expect(data.fields[1].values.get(0)).toEqual(1504108800000);
-        beforeEach(() => {
+            expect(data.fields[0].values.get(0)).toEqual(1);
-          options.targets[0].appInsights.groupBy = 'client/city';
+            expect(data.fields[1].values.get(1)).toEqual(1504112400000);
-          options.targets[0].appInsights.alias = '{{metric}} + {{groupbyname}} + {{groupbyvalue}}';
+            expect(data.fields[0].values.get(1)).toEqual(2);
-
-          ctx.backendSrv.datasourceRequest = (options: { url: string }) => {
-            expect(options.url).toContain('/metrics/exceptions/server');
-            expect(options.url).toContain('segment=client/city');
-            return ctx.$q.when({ data: response, status: 200 });
-          };
-        });
-
-        it('should return a list of datapoints', () => {
-          return ctx.ds.query(options).then((results: any) => {
-            expect(results.data.length).toBe(3);
-            expect(results.data[0].datapoints.length).toBe(2);
-            expect(results.data[0].target).toEqual('exceptions/server + client/city + Miami');
-            expect(results.data[0].datapoints[0][1]).toEqual(1504108800000);
-            expect(results.data[0].datapoints[0][0]).toEqual(10);
-            expect(results.data[0].datapoints[1][1]).toEqual(1504112400000);
-            expect(results.data[0].datapoints[1][0]).toEqual(20);
           });
         });
       });

public/app/plugins/datasource/grafana-azure-monitor-datasource/app_insights/app_insights_datasource.ts

@@ -1,12 +1,12 @@
-import _ from 'lodash';
+import { TimeSeries, toDataFrame } from '@grafana/data';
-import AppInsightsQuerystringBuilder from './app_insights_querystring_builder';
+import { DataQueryRequest, DataQueryResponseData, DataSourceInstanceSettings } from '@grafana/ui';
-import LogAnalyticsQuerystringBuilder from '../log_analytics/querystring_builder';
-import ResponseParser from './response_parser';
-import { DataSourceInstanceSettings } from '@grafana/ui';
-import { AzureDataSourceJsonData } from '../types';
 import { BackendSrv } from 'app/core/services/backend_srv';
 import { TemplateSrv } from 'app/features/templating/template_srv';
-import { IQService } from 'angular';
+import _ from 'lodash';
+
+import TimegrainConverter from '../time_grain_converter';
+import { AzureDataSourceJsonData, AzureMonitorQuery } from '../types';
+import ResponseParser from './response_parser';
 
 export interface LogAnalyticsColumn {
   text: string;
@@ -24,8 +24,7 @@ export default class AppInsightsDatasource {
   constructor(
     instanceSettings: DataSourceInstanceSettings<AzureDataSourceJsonData>,
     private backendSrv: BackendSrv,
-    private templateSrv: TemplateSrv,
+    private templateSrv: TemplateSrv
-    private $q: IQService
   ) {
     this.id = instanceSettings.id;
     this.applicationId = instanceSettings.jsonData.appInsightsAppId;
@@ -37,73 +36,82 @@ export default class AppInsightsDatasource {
     return !!this.applicationId && this.applicationId.length > 0;
   }
 
-  query(options: any) {
+  createRawQueryRequest(item: any, options: DataQueryRequest<AzureMonitorQuery>, target: AzureMonitorQuery) {
+    if (item.xaxis && !item.timeColumn) {
+      item.timeColumn = item.xaxis;
+    }
+
+    if (item.yaxis && !item.valueColumn) {
+      item.valueColumn = item.yaxis;
+    }
+
+    if (item.spliton && !item.segmentColumn) {
+      item.segmentColumn = item.spliton;
+    }
+
+    return {
+      type: 'timeSeriesQuery',
+      raw: false,
+      appInsights: {
+        rawQuery: true,
+        rawQueryString: this.templateSrv.replace(item.rawQueryString, options.scopedVars),
+        timeColumn: item.timeColumn,
+        valueColumn: item.valueColumn,
+        segmentColumn: item.segmentColumn,
+      },
+    };
+  }
+
+  createMetricsRequest(item: any, options: DataQueryRequest<AzureMonitorQuery>, target: AzureMonitorQuery) {
+    // fix for timeGrainUnit which is a deprecated/removed field name
+    if (item.timeGrainCount) {
+      item.timeGrain = TimegrainConverter.createISO8601Duration(item.timeGrainCount, item.timeGrainUnit);
+    } else if (item.timeGrainUnit && item.timeGrain !== 'auto') {
+      item.timeGrain = TimegrainConverter.createISO8601Duration(item.timeGrain, item.timeGrainUnit);
+    }
+
+    // migration for non-standard names
+    if (item.groupBy && !item.dimension) {
+      item.dimension = item.groupBy;
+    }
+
+    if (item.filter && !item.dimensionFilter) {
+      item.dimensionFilter = item.filter;
+    }
+
+    return {
+      type: 'timeSeriesQuery',
+      raw: false,
+      appInsights: {
+        rawQuery: false,
+        timeGrain: this.templateSrv.replace((item.timeGrain || '').toString(), options.scopedVars),
+        allowedTimeGrainsMs: item.allowedTimeGrainsMs,
+        metricName: this.templateSrv.replace(item.metricName, options.scopedVars),
+        aggregation: this.templateSrv.replace(item.aggregation, options.scopedVars),
+        dimension: this.templateSrv.replace(item.dimension, options.scopedVars),
+        dimensionFilter: this.templateSrv.replace(item.dimensionFilter, options.scopedVars),
+        alias: item.alias,
+        format: target.format,
+      },
+    };
+  }
+
+  async query(options: DataQueryRequest<AzureMonitorQuery>): Promise<DataQueryResponseData[]> {
     const queries = _.filter(options.targets, item => {
       return item.hide !== true;
-    }).map(target => {
+    }).map((target: AzureMonitorQuery) => {
       const item = target.appInsights;
+      let query: any;
       if (item.rawQuery) {
-        const querystringBuilder = new LogAnalyticsQuerystringBuilder(
+        query = this.createRawQueryRequest(item, options, target);
-          this.templateSrv.replace(item.rawQueryString, options.scopedVars),
-          options,
-          'timestamp'
-        );
-        const generated = querystringBuilder.generate();
-
-        const url = `${this.baseUrl}/query?${generated.uriString}`;
-
-        return {
-          refId: target.refId,
-          intervalMs: options.intervalMs,
-          maxDataPoints: options.maxDataPoints,
-          datasourceId: this.id,
-          url: url,
-          format: options.format,
-          alias: item.alias,
-          query: generated.rawQuery,
-          xaxis: item.xaxis,
-          yaxis: item.yaxis,
-          spliton: item.spliton,
-          raw: true,
-        };
       } else {
-        const querystringBuilder = new AppInsightsQuerystringBuilder(
+        query = this.createMetricsRequest(item, options, target);
-          options.range.from,
-          options.range.to,
-          options.interval
-        );
-
-        if (item.groupBy !== 'none') {
-          querystringBuilder.setGroupBy(this.templateSrv.replace(item.groupBy, options.scopedVars));
-        }
-        querystringBuilder.setAggregation(item.aggregation);
-        querystringBuilder.setInterval(
-          item.timeGrainType,
-          this.templateSrv.replace(item.timeGrain, options.scopedVars),
-          item.timeGrainUnit
-        );
-
-        querystringBuilder.setFilter(this.templateSrv.replace(item.filter || ''));
-
-        const url = `${this.baseUrl}/metrics/${this.templateSrv.replace(
-          encodeURI(item.metricName),
-          options.scopedVars
-        )}?${querystringBuilder.generate()}`;
-
-        return {
-          refId: target.refId,
-          intervalMs: options.intervalMs,
-          maxDataPoints: options.maxDataPoints,
-          datasourceId: this.id,
-          url: url,
-          format: options.format,
-          alias: item.alias,
-          xaxis: '',
-          yaxis: '',
-          spliton: '',
-          raw: false,
-        };
       }
+      query.refId = target.refId;
+      query.intervalMs = options.intervalMs;
+      query.datasourceId = this.id;
+      query.queryType = 'Application Insights';
+      return query;
     });
 
     if (!queries || queries.length === 0) {
@@ -111,25 +119,42 @@ export default class AppInsightsDatasource {
       return;
     }
 
-    const promises = this.doQueries(queries);
+    const { data } = await this.backendSrv.datasourceRequest({
+      url: '/api/tsdb/query',
+      method: 'POST',
+      data: {
+        from: options.range.from.valueOf().toString(),
+        to: options.range.to.valueOf().toString(),
+        queries,
+      },
+    });
 
-    return this.$q
+    const result: DataQueryResponseData[] = [];
-      .all(promises)
+    if (data.results) {
-      .then(results => {
+      Object.values(data.results).forEach((queryRes: any) => {
-        return new ResponseParser(results).parseQueryResult();
+        if (queryRes.meta && queryRes.meta.columns) {
-      })
+          const columnNames = queryRes.meta.columns as string[];
-      .then(results => {
+          this.logAnalyticsColumns[queryRes.refId] = _.map(columnNames, n => ({ text: n, value: n }));
-        const flattened: any[] = [];
-
-        for (let i = 0; i < results.length; i++) {
-          if (results[i].columnsForDropdown) {
-            this.logAnalyticsColumns[results[i].refId] = results[i].columnsForDropdown;
-          }
-          flattened.push(results[i]);
         }
 
-        return flattened;
+        if (!queryRes.series) {
+          return;
+        }
+
+        queryRes.series.forEach((series: any) => {
+          const timeSerie: TimeSeries = {
+            target: series.name,
+            datapoints: series.points,
+            refId: queryRes.refId,
+            meta: queryRes.meta,
+          };
+          result.push(toDataFrame(timeSerie));
+        });
       });
+      return result;
+    }
+
+    return Promise.resolve([]);
   }
 
   doQueries(queries: any) {

public/app/plugins/datasource/grafana-azure-monitor-datasource/app_insights/app_insights_querystring_builder.test.ts

@@ -1,72 +0,0 @@
-import AppInsightsQuerystringBuilder from './app_insights_querystring_builder';
-import { toUtc } from '@grafana/data';
-
-describe('AppInsightsQuerystringBuilder', () => {
-  let builder: AppInsightsQuerystringBuilder;
-
-  beforeEach(() => {
-    builder = new AppInsightsQuerystringBuilder(toUtc('2017-08-22 06:00'), toUtc('2017-08-22 07:00'), '1h');
-  });
-
-  describe('with only from/to date range', () => {
-    it('should always add datetime filtering to the querystring', () => {
-      const querystring = `timespan=2017-08-22T06:00:00Z/2017-08-22T07:00:00Z`;
-      expect(builder.generate()).toEqual(querystring);
-    });
-  });
-
-  describe('with from/to date range and aggregation type', () => {
-    beforeEach(() => {
-      builder.setAggregation('avg');
-    });
-
-    it('should add datetime filtering and aggregation to the querystring', () => {
-      const querystring = `timespan=2017-08-22T06:00:00Z/2017-08-22T07:00:00Z&aggregation=avg`;
-      expect(builder.generate()).toEqual(querystring);
-    });
-  });
-
-  describe('with from/to date range and group by segment', () => {
-    beforeEach(() => {
-      builder.setGroupBy('client/city');
-    });
-
-    it('should add datetime filtering and segment to the querystring', () => {
-      const querystring = `timespan=2017-08-22T06:00:00Z/2017-08-22T07:00:00Z&segment=client/city`;
-      expect(builder.generate()).toEqual(querystring);
-    });
-  });
-
-  describe('with from/to date range and specific group by interval', () => {
-    beforeEach(() => {
-      builder.setInterval('specific', 1, 'hour');
-    });
-
-    it('should add datetime filtering and interval to the querystring', () => {
-      const querystring = `timespan=2017-08-22T06:00:00Z/2017-08-22T07:00:00Z&interval=PT1H`;
-      expect(builder.generate()).toEqual(querystring);
-    });
-  });
-
-  describe('with from/to date range and auto group by interval', () => {
-    beforeEach(() => {
-      builder.setInterval('auto', '', '');
-    });
-
-    it('should add datetime filtering and interval to the querystring', () => {
-      const querystring = `timespan=2017-08-22T06:00:00Z/2017-08-22T07:00:00Z&interval=PT1H`;
-      expect(builder.generate()).toEqual(querystring);
-    });
-  });
-
-  describe('with filter', () => {
-    beforeEach(() => {
-      builder.setFilter(`client/city eq 'Boydton'`);
-    });
-
-    it('should add datetime filtering and interval to the querystring', () => {
-      const querystring = `timespan=2017-08-22T06:00:00Z/2017-08-22T07:00:00Z&filter=client/city eq 'Boydton'`;
-      expect(builder.generate()).toEqual(querystring);
-    });
-  });
-});

public/app/plugins/datasource/grafana-azure-monitor-datasource/app_insights/app_insights_querystring_builder.ts

@@ -1,56 +0,0 @@
-import TimeGrainConverter from '../time_grain_converter';
-
-export default class AppInsightsQuerystringBuilder {
-  aggregation = '';
-  groupBy = '';
-  timeGrainType = '';
-  timeGrain = '';
-  timeGrainUnit = '';
-  filter = '';
-
-  constructor(private from: any, private to: any, public grafanaInterval: any) {}
-
-  setAggregation(aggregation: string) {
-    this.aggregation = aggregation;
-  }
-
-  setGroupBy(groupBy: string) {
-    this.groupBy = groupBy;
-  }
-
-  setInterval(timeGrainType: string, timeGrain: any, timeGrainUnit: string) {
-    this.timeGrainType = timeGrainType;
-    this.timeGrain = timeGrain;
-    this.timeGrainUnit = timeGrainUnit;
-  }
-
-  setFilter(filter: string) {
-    this.filter = filter;
-  }
-
-  generate() {
-    let querystring = `timespan=${this.from.utc().format()}/${this.to.utc().format()}`;
-
-    if (this.aggregation && this.aggregation.length > 0) {
-      querystring += `&aggregation=${this.aggregation}`;
-    }
-
-    if (this.groupBy && this.groupBy.length > 0) {
-      querystring += `&segment=${this.groupBy}`;
-    }
-
-    if (this.timeGrainType === 'specific' && this.timeGrain && this.timeGrainUnit) {
-      querystring += `&interval=${TimeGrainConverter.createISO8601Duration(this.timeGrain, this.timeGrainUnit)}`;
-    }
-
-    if (this.timeGrainType === 'auto') {
-      querystring += `&interval=${TimeGrainConverter.createISO8601DurationFromInterval(this.grafanaInterval)}`;
-    }
-
-    if (this.filter) {
-      querystring += `&filter=${this.filter}`;
-    }
-
-    return querystring;
-  }
-}

public/app/plugins/datasource/grafana-azure-monitor-datasource/datasource.ts

@@ -22,12 +22,7 @@ export default class Datasource extends DataSourceApi<AzureMonitorQuery, AzureDa
   ) {
     super(instanceSettings);
     this.azureMonitorDatasource = new AzureMonitorDatasource(instanceSettings, this.backendSrv, this.templateSrv);
-    this.appInsightsDatasource = new AppInsightsDatasource(
+    this.appInsightsDatasource = new AppInsightsDatasource(instanceSettings, this.backendSrv, this.templateSrv);
-      instanceSettings,
-      this.backendSrv,
-      this.templateSrv,
-      this.$q
-    );
 
     this.azureLogAnalyticsDatasource = new AzureLogAnalyticsDatasource(
       instanceSettings,

public/app/plugins/datasource/grafana-azure-monitor-datasource/partials/query.editor.html

@@ -48,7 +48,7 @@
           get-options="ctrl.getMetricNamespaces($query)" on-change="ctrl.onMetricNamespacesChange()" css-class="min-width-12">
         </gf-form-dropdown>
       </div>
-      <div class="gf-form">        
+      <div class="gf-form">
         <label class="gf-form-label query-keyword width-9">Metric</label>
         <gf-form-dropdown model="ctrl.target.azureMonitor.metricName" allow-custom="true" lookup-text="true"
           get-options="ctrl.getMetricNames($query)" on-change="ctrl.onMetricNameChange()" css-class="min-width-12">
@@ -62,7 +62,7 @@
         </div>
       </div>
     </div>
-    <div class="gf-form-inline">      
+    <div class="gf-form-inline">
       <div class="gf-form">
         <label class="gf-form-label query-keyword width-9">Time Grain</label>
         <div class="gf-form-select-wrapper gf-form-select-wrapper--caret-indent timegrainunit-dropdown-wrapper">
@@ -72,7 +72,7 @@
       </div>
       <div class="gf-form" ng-show="ctrl.target.azureMonitor.timeGrain.trim() === 'auto'">
         <label class="gf-form-label">Auto Interval</label>
-        <label class="gf-form-label">{{ctrl.getAutoInterval()}}</label>
+        <label class="gf-form-label">{{ctrl.getAzureMonitorAutoInterval()}}</label>
       </div>
       <div class="gf-form gf-form--grow">
         <div class="gf-form-label gf-form-label--grow"></div>
@@ -238,19 +238,19 @@
       <div class="gf-form-inline">
         <div class="gf-form">
           <label class="gf-form-label query-keyword width-9">Group By</label>
-          <gf-form-dropdown allow-custom="true" ng-hide="ctrl.target.appInsights.groupBy !== 'none'" model="ctrl.target.appInsights.groupBy"
+          <gf-form-dropdown allow-custom="true" ng-hide="ctrl.target.appInsights.dimension !== 'none'" model="ctrl.target.appInsights.dimension"
             lookup-text="true" get-options="ctrl.getAppInsightsGroupBySegments($query)" on-change="ctrl.refresh()"
             css-class="min-width-20">
           </gf-form-dropdown>
-          <label class="gf-form-label min-width-20 pointer" ng-hide="ctrl.target.appInsights.groupBy === 'none'"
+          <label class="gf-form-label min-width-20 pointer" ng-hide="ctrl.target.appInsights.dimension === 'none'"
-            ng-click="ctrl.resetAppInsightsGroupBy()">{{ctrl.target.appInsights.groupBy}}
+            ng-click="ctrl.resetAppInsightsGroupBy()">{{ctrl.target.appInsights.dimension}}
             <i class="fa fa-remove"></i>
           </label>
         </div>
         <div class="gf-form-inline">
           <div class="gf-form">
             <label class="gf-form-label query-keyword width-9">Filter</label>
-            <input type="text" class="gf-form-input width-17" ng-model="ctrl.target.appInsights.filter" spellcheck="false"
+            <input type="text" class="gf-form-input width-17" ng-model="ctrl.target.appInsights.dimensionFilter" spellcheck="false"
               placeholder="your/groupby eq 'a_value'" ng-blur="ctrl.refresh()">
           </div>
         </div>
@@ -258,7 +258,6 @@
           <div class="gf-form-label gf-form-label--grow"></div>
         </div>
       </div>
-
       <div class="gf-form-inline">
         <div class="gf-form">
           <label class="gf-form-label query-keyword width-9">Time Grain</label>
@@ -268,17 +267,17 @@
           </div>
         </div>
         <div class="gf-form" ng-hide="ctrl.target.appInsights.timeGrainType === 'auto' || ctrl.target.appInsights.timeGrainType === 'none'">
-          <input type="text" class="gf-form-input width-3" ng-model="ctrl.target.appInsights.timeGrain" spellcheck="false"
+          <input type="text" class="gf-form-input width-3" ng-model="ctrl.target.appInsights.timeGrainCount" spellcheck="false"
-            placeholder="" ng-blur="ctrl.refresh()">
+            placeholder="" ng-blur="ctrl.updateAppInsightsTimeGrain()">
         </div>
         <div class="gf-form" ng-hide="ctrl.target.appInsights.timeGrainType === 'auto' || ctrl.target.appInsights.timeGrainType === 'none'">
-          <div class="gf-form-select-wrapper gf-form-select-wrapper--caret-indent timegrainunit-dropdown-wrapper">
+            <div class="gf-form-select-wrapper gf-form-select-wrapper--caret-indent timegrainunit-dropdown-wrapper">
             <select class="gf-form-input" ng-model="ctrl.target.appInsights.timeGrainUnit" ng-options="f as f for f in ['minute', 'hour', 'day', 'month', 'year']"
-              ng-change="ctrl.refresh()"></select>
+                ng-change="ctrl.updateAppInsightsTimeGrain()"></select>
+            </div>
           </div>
-        </div>
         <div class="gf-form" ng-hide="ctrl.target.appInsights.timeGrainType !== 'auto'">
-          <label class="gf-form-label">Auto Interval</label>
+            <label class="gf-form-label">Auto Interval</label>
           <label class="gf-form-label">{{ctrl.getAppInsightsAutoInterval()}}</label>
         </div>
         <div class="gf-form gf-form--grow">
@@ -291,10 +290,9 @@
           <input type="text" class="gf-form-input width-30" ng-model="ctrl.target.appInsights.alias" spellcheck="false"
             placeholder="alias patterns (see help for more info)" ng-blur="ctrl.refresh()">
         </div>
-
+      </div>
-        <div class="gf-form gf-form--grow">
+      <div class="gf-form gf-form--grow">
-          <div class="gf-form-label gf-form-label--grow"></div>
+        <div class="gf-form-label gf-form-label--grow"></div>
-        </div>
       </div>
     </div>
     <div ng-show="ctrl.target.appInsights.rawQuery">
@@ -316,13 +314,13 @@
       <div class="gf-form-inline">
         <div class="gf-form">
           <label class="gf-form-label query-keyword width-9">X-axis</label>
-          <gf-form-dropdown model="ctrl.target.appInsights.xaxis" allow-custom="true" placeholder="eg. 'timestamp'"
+          <gf-form-dropdown model="ctrl.target.appInsights.timeColumn" allow-custom="true" placeholder="eg. 'timestamp'"
             get-options="ctrl.getAppInsightsColumns($query)" on-change="ctrl.onAppInsightsColumnChange()" css-class="min-width-20">
           </gf-form-dropdown>
         </div>
         <div class="gf-form">
-          <label class="gf-form-label query-keyword width-9">Y-axis(es)</label>
+          <label class="gf-form-label query-keyword width-9">Y-axis</label>
-          <gf-form-dropdown model="ctrl.target.appInsights.yaxis" allow-custom="true" get-options="ctrl.getAppInsightsColumns($query)"
+          <gf-form-dropdown model="ctrl.target.appInsights.valueColumn" allow-custom="true" get-options="ctrl.getAppInsightsColumns($query)"
             on-change="ctrl.onAppInsightsColumnChange()" css-class="min-width-20">
           </gf-form-dropdown>
         </div>
@@ -333,7 +331,7 @@
       <div class="gf-form-inline">
         <div class="gf-form">
           <label class="gf-form-label query-keyword width-9">Split On</label>
-          <gf-form-dropdown model="ctrl.target.appInsights.spliton" allow-custom="true" get-options="ctrl.getAppInsightsColumns($query)"
+          <gf-form-dropdown model="ctrl.target.appInsights.segmentColumn" allow-custom="true" get-options="ctrl.getAppInsightsColumns($query)"
             on-change="ctrl.onAppInsightsColumnChange()" css-class="min-width-20">
           </gf-form-dropdown>
         </div>

public/app/plugins/datasource/grafana-azure-monitor-datasource/query_ctrl.test.ts

@@ -41,7 +41,7 @@ describe('AzureMonitorQueryCtrl', () => {
       expect(queryCtrl.target.azureMonitor.resourceName).toBe('select');
       expect(queryCtrl.target.azureMonitor.metricNamespace).toBe('select');
       expect(queryCtrl.target.azureMonitor.metricName).toBe('select');
-      expect(queryCtrl.target.appInsights.groupBy).toBe('none');
+      expect(queryCtrl.target.appInsights.dimension).toBe('none');
     });
   });
 
@@ -239,6 +239,35 @@ describe('AzureMonitorQueryCtrl', () => {
   });
 
   describe('and query type is Application Insights', () => {
+    describe('and target is in old format', () => {
+      it('data is migrated', () => {
+        queryCtrl.target.appInsights.xaxis = 'sample-x';
+        queryCtrl.target.appInsights.yaxis = 'sample-y';
+        queryCtrl.target.appInsights.spliton = 'sample-split';
+        queryCtrl.target.appInsights.groupBy = 'sample-group';
+        queryCtrl.target.appInsights.groupByOptions = ['sample-group-1', 'sample-group-2'];
+        queryCtrl.target.appInsights.filter = 'sample-filter';
+        queryCtrl.target.appInsights.metricName = 'sample-metric';
+
+        queryCtrl.migrateApplicationInsightsKeys();
+
+        expect(queryCtrl.target.appInsights.xaxis).toBeUndefined();
+        expect(queryCtrl.target.appInsights.yaxis).toBeUndefined();
+        expect(queryCtrl.target.appInsights.spliton).toBeUndefined();
+        expect(queryCtrl.target.appInsights.groupBy).toBeUndefined();
+        expect(queryCtrl.target.appInsights.groupByOptions).toBeUndefined();
+        expect(queryCtrl.target.appInsights.filter).toBeUndefined();
+
+        expect(queryCtrl.target.appInsights.timeColumn).toBe('sample-x');
+        expect(queryCtrl.target.appInsights.valueColumn).toBe('sample-y');
+        expect(queryCtrl.target.appInsights.segmentColumn).toBe('sample-split');
+        expect(queryCtrl.target.appInsights.dimension).toBe('sample-group');
+        expect(queryCtrl.target.appInsights.dimensions).toEqual(['sample-group-1', 'sample-group-2']);
+        expect(queryCtrl.target.appInsights.dimensionFilter).toBe('sample-filter');
+        expect(queryCtrl.target.appInsights.metricName).toBe('sample-metric');
+      });
+    });
+
     describe('when getOptions for the Metric Names dropdown is called', () => {
       const response = [{ text: 'metric1', value: 'metric1' }, { text: 'metric2', value: 'metric2' }];
 
@@ -259,7 +288,7 @@ describe('AzureMonitorQueryCtrl', () => {
 
     describe('when getOptions for the GroupBy segments dropdown is called', () => {
       beforeEach(() => {
-        queryCtrl.target.appInsights.groupByOptions = ['opt1', 'opt2'];
+        queryCtrl.target.appInsights.dimensions = ['opt1', 'opt2'];
       });
 
       it('should return a list of GroupBy segments', () => {
@@ -291,8 +320,8 @@ describe('AzureMonitorQueryCtrl', () => {
           expect(queryCtrl.target.appInsights.aggregation).toBe('avg');
           expect(queryCtrl.target.appInsights.aggOptions).toContain('avg');
           expect(queryCtrl.target.appInsights.aggOptions).toContain('sum');
-          expect(queryCtrl.target.appInsights.groupByOptions).toContain('client/os');
+          expect(queryCtrl.target.appInsights.dimensions).toContain('client/os');
-          expect(queryCtrl.target.appInsights.groupByOptions).toContain('client/city');
+          expect(queryCtrl.target.appInsights.dimensions).toContain('client/city');
         });
       });
     });

public/app/plugins/datasource/grafana-azure-monitor-datasource/query_ctrl.ts

@@ -32,13 +32,13 @@ export class AzureMonitorQueryCtrl extends QueryCtrl {
       dimensionFilter: string;
       timeGrain: string;
       timeGrainUnit: string;
-      timeGrains: Array<{ text: string; value: string }>;
       allowedTimeGrainsMs: number[];
       dimensions: any[];
       dimension: any;
       top: string;
       aggregation: string;
       aggOptions: string[];
+      timeGrains: Array<{ text: string; value: string }>;
     };
     azureLogAnalytics: {
       query: string;
@@ -46,19 +46,28 @@ export class AzureMonitorQueryCtrl extends QueryCtrl {
       workspace: string;
     };
     appInsights: {
-      metricName: string;
       rawQuery: boolean;
-      rawQueryString: string;
+      // metric style query when rawQuery == false
-      groupBy: string;
+      metricName: string;
-      timeGrainType: string;
+      dimension: any;
-      xaxis: string;
+      dimensionFilter: string;
-      yaxis: string;
+      dimensions: string[];
-      spliton: string;
+
       aggOptions: string[];
       aggregation: string;
-      groupByOptions: string[];
+
+      timeGrainType: string;
+      timeGrainCount: string;
       timeGrainUnit: string;
       timeGrain: string;
+      timeGrains: Array<{ text: string; value: string }>;
+      allowedTimeGrainsMs: number[];
+
+      // query style query when rawQuery == true
+      rawQueryString: string;
+      timeColumn: string;
+      valueColumn: string;
+      segmentColumn: string;
     };
   };
 
@@ -73,6 +82,8 @@ export class AzureMonitorQueryCtrl extends QueryCtrl {
       dimensionFilter: '*',
       timeGrain: 'auto',
       top: '10',
+      aggOptions: [] as string[],
+      timeGrains: [] as string[],
     },
     azureLogAnalytics: {
       query: [
@@ -96,11 +107,10 @@ export class AzureMonitorQueryCtrl extends QueryCtrl {
       metricName: this.defaultDropdownValue,
       rawQuery: false,
       rawQueryString: '',
-      groupBy: 'none',
+      dimension: 'none',
-      timeGrainType: 'auto',
+      timeGrain: 'auto',
-      xaxis: 'timestamp',
+      timeColumn: 'timestamp',
-      yaxis: '',
+      valueColumn: '',
-      spliton: '',
     },
   };
 
@@ -124,6 +134,8 @@ export class AzureMonitorQueryCtrl extends QueryCtrl {
 
     this.migrateToDefaultNamespace();
 
+    this.migrateApplicationInsightsKeys();
+
     this.panelCtrl.events.on('data-received', this.onDataReceived.bind(this), $scope);
     this.panelCtrl.events.on('data-error', this.onDataError.bind(this), $scope);
     this.resultFormats = [{ text: 'Time series', value: 'time_series' }, { text: 'Table', value: 'table' }];
@@ -184,6 +196,23 @@ export class AzureMonitorQueryCtrl extends QueryCtrl {
       this.onMetricNameChange();
     }
 
+    if (this.target.appInsights.timeGrainUnit) {
+      if (this.target.appInsights.timeGrain !== 'auto') {
+        if (this.target.appInsights.timeGrainCount) {
+          this.target.appInsights.timeGrain = TimegrainConverter.createISO8601Duration(
+            this.target.appInsights.timeGrainCount,
+            this.target.appInsights.timeGrainUnit
+          );
+        } else {
+          this.target.appInsights.timeGrainCount = this.target.appInsights.timeGrain;
+          this.target.appInsights.timeGrain = TimegrainConverter.createISO8601Duration(
+            this.target.appInsights.timeGrain,
+            this.target.appInsights.timeGrainUnit
+          );
+        }
+      }
+    }
+
     if (
       this.target.azureMonitor.timeGrains &&
       this.target.azureMonitor.timeGrains.length > 0 &&
@@ -191,6 +220,14 @@ export class AzureMonitorQueryCtrl extends QueryCtrl {
     ) {
       this.target.azureMonitor.allowedTimeGrainsMs = this.convertTimeGrainsToMs(this.target.azureMonitor.timeGrains);
     }
+
+    if (
+      this.target.appInsights.timeGrains &&
+      this.target.appInsights.timeGrains.length > 0 &&
+      (!this.target.appInsights.allowedTimeGrainsMs || this.target.appInsights.allowedTimeGrainsMs.length === 0)
+    ) {
+      this.target.appInsights.allowedTimeGrainsMs = this.convertTimeGrainsToMs(this.target.appInsights.timeGrains);
+    }
   }
 
   migrateToFromTimes() {
@@ -210,6 +247,27 @@ export class AzureMonitorQueryCtrl extends QueryCtrl {
     this.target.azureMonitor.metricNamespace = this.target.azureMonitor.metricDefinition;
   }
 
+  migrateApplicationInsightsKeys(): void {
+    const appInsights = this.target.appInsights as any;
+
+    // Migrate old app insights data keys to match other datasources
+    const mappings = {
+      xaxis: 'timeColumn',
+      yaxis: 'valueColumn',
+      spliton: 'segmentColumn',
+      groupBy: 'dimension',
+      groupByOptions: 'dimensions',
+      filter: 'dimensionFilter',
+    } as { [old: string]: string };
+
+    for (const old in mappings) {
+      if (appInsights[old]) {
+        appInsights[mappings[old]] = appInsights[old];
+        delete appInsights[old];
+      }
+    }
+  }
+
   replace(variable: string) {
     return this.templateSrv.replace(variable, this.panelCtrl.panel.scopedVars);
   }
@@ -424,6 +482,7 @@ export class AzureMonitorQueryCtrl extends QueryCtrl {
         if (metadata.dimensions.length > 0) {
           this.target.azureMonitor.dimension = metadata.dimensions[0].value;
         }
+
         return this.refresh();
       })
       .catch(this.handleQueryCtrlError.bind(this));
@@ -439,19 +498,34 @@ export class AzureMonitorQueryCtrl extends QueryCtrl {
     return allowedTimeGrainsMs;
   }
 
-  getAutoInterval() {
+  generateAutoUnits(timeGrain: string, timeGrains: Array<{ value: string }>) {
-    if (this.target.azureMonitor.timeGrain === 'auto') {
+    if (timeGrain === 'auto') {
       return TimegrainConverter.findClosestTimeGrain(
         this.templateSrv.getBuiltInIntervalValue(),
-        _.map(this.target.azureMonitor.timeGrains, o =>
+        _.map(timeGrains, o => TimegrainConverter.createKbnUnitFromISO8601Duration(o.value)) || [
-          TimegrainConverter.createKbnUnitFromISO8601Duration(o.value)
+          '1m',
-        ) || ['1m', '5m', '15m', '30m', '1h', '6h', '12h', '1d']
+          '5m',
+          '15m',
+          '30m',
+          '1h',
+          '6h',
+          '12h',
+          '1d',
+        ]
       );
     }
 
     return '';
   }
 
+  getAzureMonitorAutoInterval() {
+    return this.generateAutoUnits(this.target.azureMonitor.timeGrain, this.target.azureMonitor.timeGrains);
+  }
+
+  getApplicationInsightAutoInterval() {
+    return this.generateAutoUnits(this.target.appInsights.timeGrain, this.target.appInsights.timeGrains);
+  }
+
   /* Azure Log Analytics */
 
   getWorkspaces = () => {
@@ -521,7 +595,7 @@ export class AzureMonitorQueryCtrl extends QueryCtrl {
       .getAppInsightsMetricMetadata(this.replace(this.target.appInsights.metricName))
       .then((aggData: { supportedAggTypes: string[]; supportedGroupBy: string[]; primaryAggType: string }) => {
         this.target.appInsights.aggOptions = aggData.supportedAggTypes;
-        this.target.appInsights.groupByOptions = aggData.supportedGroupBy;
+        this.target.appInsights.dimensions = aggData.supportedGroupBy;
         this.target.appInsights.aggregation = aggData.primaryAggType;
         return this.refresh();
       })
@@ -541,27 +615,41 @@ export class AzureMonitorQueryCtrl extends QueryCtrl {
   };
 
   getAppInsightsGroupBySegments(query: any) {
-    return _.map(this.target.appInsights.groupByOptions, option => {
+    return _.map(this.target.appInsights.dimensions, (option: string) => {
       return { text: option, value: option };
     });
   }
 
   resetAppInsightsGroupBy() {
-    this.target.appInsights.groupBy = 'none';
+    this.target.appInsights.dimension = 'none';
-    this.refresh();
-  }
-
-  updateTimeGrainType() {
-    if (this.target.appInsights.timeGrainType === 'specific') {
-      this.target.appInsights.timeGrain = '1';
-      this.target.appInsights.timeGrainUnit = 'minute';
-    } else {
-      this.target.appInsights.timeGrain = '';
-    }
     this.refresh();
   }
 
   toggleEditorMode() {
     this.target.appInsights.rawQuery = !this.target.appInsights.rawQuery;
   }
+
+  updateTimeGrainType() {
+    if (this.target.appInsights.timeGrainType === 'specific') {
+      this.target.appInsights.timeGrainCount = '1';
+      this.target.appInsights.timeGrainUnit = 'minute';
+      this.target.appInsights.timeGrain = TimegrainConverter.createISO8601Duration(
+        this.target.appInsights.timeGrainCount,
+        this.target.appInsights.timeGrainUnit
+      );
+    } else {
+      this.target.appInsights.timeGrainCount = '';
+      this.target.appInsights.timeGrainUnit = '';
+    }
+  }
+
+  updateAppInsightsTimeGrain() {
+    if (this.target.appInsights.timeGrainUnit && this.target.appInsights.timeGrainCount) {
+      this.target.appInsights.timeGrain = TimegrainConverter.createISO8601Duration(
+        this.target.appInsights.timeGrainCount,
+        this.target.appInsights.timeGrainUnit
+      );
+    }
+    this.refresh();
+  }
 }

public/app/plugins/datasource/grafana-azure-monitor-datasource/types.ts

@@ -1,11 +1,12 @@
 import { DataQuery, DataSourceJsonData } from '@grafana/ui';
 
 export interface AzureMonitorQuery extends DataQuery {
+  refId: string;
   format: string;
   subscription: string;
   azureMonitor: AzureMetricQuery;
   azureLogAnalytics: AzureLogsQuery;
-  //   appInsights: any;
+  appInsights: ApplicationInsightsQuery;
 }
 
 export interface AzureDataSourceJsonData extends DataSourceJsonData {
@@ -35,7 +36,6 @@ export interface AzureMetricQuery {
   metricName: string;
   timeGrainUnit: string;
   timeGrain: string;
-  timeGrains: string[];
   allowedTimeGrainsMs: number[];
   aggregation: string;
   dimension: string;
@@ -50,6 +50,19 @@ export interface AzureLogsQuery {
   workspace: string;
 }
 
+export interface ApplicationInsightsQuery {
+  rawQuery: boolean;
+  rawQueryString: any;
+  metricName: string;
+  timeGrainUnit: string;
+  timeGrain: string;
+  allowedTimeGrainsMs: number[];
+  aggregation: string;
+  dimension: string;
+  dimensionFilter: string;
+  alias: string;
+}
+
 // Azure Monitor API Types
 
 export interface AzureMonitorMetricDefinitionsResponse {