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Commit 376a9d35 by Kyle Brandt Committed by GitHub
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Azure Monitor: Change response to be dataframes (#25123) 

note: This is just Azure Monitor within the Azure Monitor datasource (not insights, insights analytics, or log analytics yet).

Co-authored-by: Ryan McKinley <ryantxu@gmail.com>
parent 07582a8e
Showing with 447 additions and 467 deletions
packages/grafana-runtime/src/utils/DataSourceWithBackend.ts
......@@ -5,8 +5,9 @@ import {
DataSourceInstanceSettings,
DataQuery,
DataSourceJsonData,
ScopedVars,
} from '@grafana/data';
import { Observable, from } from 'rxjs';
import { Observable, from, of } from 'rxjs';
import { config } from '..';
import { getBackendSrv } from '../services';
import { toDataQueryResponse } from './queryResponse';
......@@ -53,9 +54,13 @@ export class DataSourceWithBackend<
/**
* Ideally final -- any other implementation may not work as expected
*/
query(request: DataQueryRequest): Observable<DataQueryResponse> {
const { targets, intervalMs, maxDataPoints, range, requestId } = request;
query(request: DataQueryRequest<TQuery>): Observable<DataQueryResponse> {
const { intervalMs, maxDataPoints, range, requestId } = request;
const orgId = config.bootData.user.orgId;
let targets = request.targets;
if (this.filterQuery) {
targets = targets.filter(q => this.filterQuery!(q));
}
const queries = targets.map(q => {
if (q.datasource === ExpressionDatasourceID) {
return {
......@@ -70,7 +75,7 @@ export class DataSourceWithBackend<
throw new Error('Unknown Datasource: ' + q.datasource);
}
return {
...this.applyTemplateVariables(q),
...this.applyTemplateVariables(q, request.scopedVars),
datasourceId: ds.id,
intervalMs,
maxDataPoints,
......@@ -78,6 +83,11 @@ export class DataSourceWithBackend<
};
});
// Return early if no queries exist
if (!queries.length) {
return of({ data: [] });
}
const body: any = {
queries,
};
......@@ -106,11 +116,18 @@ export class DataSourceWithBackend<
}
/**
* Override to skip executing a query
*
* @virtual
*/
filterQuery?(query: TQuery): boolean;
/**
* Override to apply template variables
*
* @virtual
*/
applyTemplateVariables(query: DataQuery) {
applyTemplateVariables(query: TQuery, scopedVars: ScopedVars): Record<string, any> {
return query;
}
......
pkg/tsdb/azuremonitor/azuremonitor-datasource.go
......@@ -12,6 +12,7 @@ import (
"strings"
"time"
"github.com/grafana/grafana-plugin-sdk-go/data"
"github.com/grafana/grafana/pkg/api/pluginproxy"
"github.com/grafana/grafana/pkg/models"
"github.com/grafana/grafana/pkg/plugins"
......@@ -20,7 +21,6 @@ import (
opentracing "github.com/opentracing/opentracing-go"
"golang.org/x/net/context/ctxhttp"
"github.com/grafana/grafana/pkg/components/null"
"github.com/grafana/grafana/pkg/components/simplejson"
"github.com/grafana/grafana/pkg/tsdb"
)
......@@ -260,25 +260,32 @@ func (e *AzureMonitorDatasource) unmarshalResponse(res *http.Response) (AzureMon
return data, nil
}
func (e *AzureMonitorDatasource) parseResponse(queryRes *tsdb.QueryResult, data AzureMonitorResponse, query *AzureMonitorQuery) error {
if len(data.Value) == 0 {
func (e *AzureMonitorDatasource) parseResponse(queryRes *tsdb.QueryResult, amr AzureMonitorResponse, query *AzureMonitorQuery) error {
if len(amr.Value) == 0 {
return nil
}
for _, series := range data.Value[0].Timeseries {
points := []tsdb.TimePoint{}
for _, series := range amr.Value[0].Timeseries {
metadataName := ""
metadataValue := ""
if len(series.Metadatavalues) > 0 {
metadataName = series.Metadatavalues[0].Name.LocalizedValue
metadataValue = series.Metadatavalues[0].Value
}
metricName := formatAzureMonitorLegendKey(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"], amr.Value[0].Name.LocalizedValue, metadataName, metadataValue, amr.Namespace, amr.Value[0].ID)
frame := data.NewFrameOfFieldTypes("", len(series.Data), data.FieldTypeTime, data.FieldTypeFloat64)
frame.RefID = query.RefID
frame.Fields[1].Name = metricName
frame.Fields[1].SetConfig(&data.FieldConfig{
Unit: amr.Value[0].Unit,
})
for _, point := range series.Data {
requestedAgg := query.Params.Get("aggregation")
for i, point := range series.Data {
var value float64
switch query.Params.Get("aggregation") {
switch requestedAgg {
case "Average":
value = point.Average
case "Total":
......@@ -292,15 +299,17 @@ func (e *AzureMonitorDatasource) parseResponse(queryRes *tsdb.QueryResult, data
default:
value = point.Count
}
points = append(points, tsdb.NewTimePoint(null.FloatFrom(value), float64((point.TimeStamp).Unix())*1000))
frame.SetRow(i, point.TimeStamp, value)
}
queryRes.Series = append(queryRes.Series, &tsdb.TimeSeries{
Name: metricName,
Points: points,
})
encodedFrame, err := frame.MarshalArrow()
if err != nil {
queryRes.Error = fmt.Errorf("failed to encode dataframe response into arrow: %w", err)
}
queryRes.Dataframes = append(queryRes.Dataframes, encodedFrame)
}
queryRes.Meta.Set("unit", data.Value[0].Unit)
return nil
}
......
pkg/tsdb/azuremonitor/azuremonitor-datasource_test.go
......@@ -9,314 +9,303 @@ import (
"testing"
"time"
"github.com/google/go-cmp/cmp"
"github.com/google/go-cmp/cmp/cmpopts"
"github.com/grafana/grafana-plugin-sdk-go/data"
"github.com/grafana/grafana/pkg/components/simplejson"
"github.com/grafana/grafana/pkg/models"
"github.com/grafana/grafana/pkg/tsdb"
. "github.com/smartystreets/goconvey/convey"
"github.com/stretchr/testify/require"
)
func TestAzureMonitorDatasource(t *testing.T) {
Convey("AzureMonitorDatasource", t, func() {
func TestAzureMonitorBuildQueries(t *testing.T) {
datasource := &AzureMonitorDatasource{}
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{
tests := []struct {
name string
azureMonitorVariedProperties map[string]interface{}
azureMonitorQueryTarget string
expectedInterval string
queryIntervalMS int64
}{
{
DataSource: &models.DataSource{
JsonData: simplejson.NewFromAny(map[string]interface{}{
"subscriptionId": "default-subscription",
}),
},
Model: simplejson.NewFromAny(map[string]interface{}{
"subscription": "12345678-aaaa-bbbb-cccc-123456789abc",
"azureMonitor": map[string]interface{}{
name: "Parse queries from frontend and build AzureMonitor API queries",
azureMonitorVariedProperties: map[string]interface{}{
"timeGrain": "PT1M",
"aggregation": "Average",
"resourceGroup": "grafanastaging",
"resourceName": "grafana",
"metricDefinition": "Microsoft.Compute/virtualMachines",
"metricNamespace": "Microsoft.Compute-virtualMachines",
"metricName": "Percentage CPU",
"top": "10",
"alias": "testalias",
"queryType": "Azure Monitor",
},
}),
RefId: "A",
},
expectedInterval: "PT1M",
azureMonitorQueryTarget: "aggregation=Average&api-version=2018-01-01&interval=PT1M&metricnames=Percentage+CPU&metricnamespace=Microsoft.Compute-virtualMachines&timespan=2018-03-15T13%3A00%3A00Z%2F2018-03-15T13%3A34%3A00Z",
},
}
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].URL, ShouldEqual, "12345678-aaaa-bbbb-cccc-123456789abc/resourceGroups/grafanastaging/providers/Microsoft.Compute/virtualMachines/grafana/providers/microsoft.insights/metrics")
So(queries[0].Target, ShouldEqual, "aggregation=Average&api-version=2018-01-01&interval=PT1M&metricnames=Percentage+CPU&metricnamespace=Microsoft.Compute-virtualMachines&timespan=2018-03-15T13%3A00%3A00Z%2F2018-03-15T13%3A34%3A00Z")
So(len(queries[0].Params), ShouldEqual, 6)
So(queries[0].Params["timespan"][0], ShouldEqual, "2018-03-15T13:00:00Z/2018-03-15T13:34:00Z")
So(queries[0].Params["api-version"][0], ShouldEqual, "2018-01-01")
So(queries[0].Params["aggregation"][0], ShouldEqual, "Average")
So(queries[0].Params["metricnames"][0], ShouldEqual, "Percentage CPU")
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{}{
"azureMonitor": map[string]interface{}{
{
name: "time grain set to auto",
azureMonitorVariedProperties: map[string]interface{}{
"timeGrain": "auto",
"aggregation": "Average",
"resourceGroup": "grafanastaging",
"resourceName": "grafana",
"metricDefinition": "Microsoft.Compute/virtualMachines",
"metricNamespace": "Microsoft.Compute-virtualMachines",
"metricName": "Percentage CPU",
"alias": "testalias",
"queryType": "Azure Monitor",
"top": "10",
},
})
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{}{
"azureMonitor": map[string]interface{}{
queryIntervalMS: 400000,
expectedInterval: "PT15M",
azureMonitorQueryTarget: "aggregation=Average&api-version=2018-01-01&interval=PT15M&metricnames=Percentage+CPU&metricnamespace=Microsoft.Compute-virtualMachines&timespan=2018-03-15T13%3A00%3A00Z%2F2018-03-15T13%3A34%3A00Z",
},
{
name: "time grain set to auto",
azureMonitorVariedProperties: map[string]interface{}{
"timeGrain": "auto",
"aggregation": "Average",
"resourceGroup": "grafanastaging",
"resourceName": "grafana",
"metricDefinition": "Microsoft.Compute/virtualMachines",
"metricNamespace": "Microsoft.Compute-virtualMachines",
"metricName": "Percentage CPU",
"alias": "testalias",
"queryType": "Azure Monitor",
"allowedTimeGrainsMs": []int64{60000, 300000},
"top": "10",
},
})
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{}{
"azureMonitor": map[string]interface{}{
queryIntervalMS: 400000,
expectedInterval: "PT5M",
azureMonitorQueryTarget: "aggregation=Average&api-version=2018-01-01&interval=PT5M&metricnames=Percentage+CPU&metricnamespace=Microsoft.Compute-virtualMachines&timespan=2018-03-15T13%3A00%3A00Z%2F2018-03-15T13%3A34%3A00Z",
},
{
name: "has a dimension filter",
azureMonitorVariedProperties: map[string]interface{}{
"timeGrain": "PT1M",
"aggregation": "Average",
"resourceGroup": "grafanastaging",
"resourceName": "grafana",
"metricDefinition": "Microsoft.Compute/virtualMachines",
"metricNamespace": "Microsoft.Compute-virtualMachines",
"metricName": "Percentage CPU",
"alias": "testalias",
"queryType": "Azure Monitor",
"dimension": "blob",
"dimensionFilter": "*",
"top": "30",
},
})
queries, err := datasource.buildQueries(tsdbQuery.Queries, tsdbQuery.TimeRange)
So(err, ShouldBeNil)
So(queries[0].Target, ShouldEqual, "%24filter=blob+eq+%27%2A%27&aggregation=Average&api-version=2018-01-01&interval=PT1M&metricnames=Percentage+CPU&metricnamespace=Microsoft.Compute-virtualMachines&timespan=2018-03-15T13%3A00%3A00Z%2F2018-03-15T13%3A34%3A00Z&top=30")
})
Convey("and has a dimension filter set to None", func() {
tsdbQuery.Queries[0].Model = simplejson.NewFromAny(map[string]interface{}{
"azureMonitor": map[string]interface{}{
queryIntervalMS: 400000,
expectedInterval: "PT1M",
azureMonitorQueryTarget: "%24filter=blob+eq+%27%2A%27&aggregation=Average&api-version=2018-01-01&interval=PT1M&metricnames=Percentage+CPU&metricnamespace=Microsoft.Compute-virtualMachines&timespan=2018-03-15T13%3A00%3A00Z%2F2018-03-15T13%3A34%3A00Z&top=30",
},
{
name: "has a dimension filter",
azureMonitorVariedProperties: map[string]interface{}{
"timeGrain": "PT1M",
"dimension": "None",
"dimensionFilter": "*",
"top": "10",
},
queryIntervalMS: 400000,
expectedInterval: "PT1M",
azureMonitorQueryTarget: "aggregation=Average&api-version=2018-01-01&interval=PT1M&metricnames=Percentage+CPU&metricnamespace=Microsoft.Compute-virtualMachines&timespan=2018-03-15T13%3A00%3A00Z%2F2018-03-15T13%3A34%3A00Z",
},
}
commonAzureModelProps := map[string]interface{}{
"aggregation": "Average",
"resourceGroup": "grafanastaging",
"resourceName": "grafana",
"metricDefinition": "Microsoft.Compute/virtualMachines",
"metricNamespace": "Microsoft.Compute-virtualMachines",
"metricName": "Percentage CPU",
"alias": "testalias",
"queryType": "Azure Monitor",
"dimension": "None",
"dimensionFilter": "*",
"top": "10",
},
})
}
queries, err := datasource.buildQueries(tsdbQuery.Queries, tsdbQuery.TimeRange)
So(err, ShouldBeNil)
for _, tt := range tests {
t.Run(tt.name, func(t *testing.T) {
for k, v := range commonAzureModelProps {
tt.azureMonitorVariedProperties[k] = v
}
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{}{
"subscriptionId": "default-subscription",
}),
},
Model: simplejson.NewFromAny(map[string]interface{}{
"subscription": "12345678-aaaa-bbbb-cccc-123456789abc",
"azureMonitor": tt.azureMonitorVariedProperties,
},
),
RefId: "A",
IntervalMs: tt.queryIntervalMS,
},
},
}
So(queries[0].Target, ShouldEqual, "aggregation=Average&api-version=2018-01-01&interval=PT1M&metricnames=Percentage+CPU&metricnamespace=Microsoft.Compute-virtualMachines&timespan=2018-03-15T13%3A00%3A00Z%2F2018-03-15T13%3A34%3A00Z")
azureMonitorQuery := &AzureMonitorQuery{
URL: "12345678-aaaa-bbbb-cccc-123456789abc/resourceGroups/grafanastaging/providers/Microsoft.Compute/virtualMachines/grafana/providers/microsoft.insights/metrics",
UrlComponents: map[string]string{
"metricDefinition": "Microsoft.Compute/virtualMachines",
"resourceGroup": "grafanastaging",
"resourceName": "grafana",
"subscription": "12345678-aaaa-bbbb-cccc-123456789abc",
},
Target: tt.azureMonitorQueryTarget,
RefID: "A",
Alias: "testalias",
}
queries, err := datasource.buildQueries(tsdbQuery.Queries, tsdbQuery.TimeRange)
if err != nil {
t.Error(err)
}
if diff := cmp.Diff(azureMonitorQuery, queries[0], cmpopts.IgnoreUnexported(simplejson.Json{}), cmpopts.IgnoreFields(AzureMonitorQuery{}, "Params")); diff != "" {
t.Errorf("Result mismatch (-want +got):\n%s", diff)
}
})
})
}
}
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("azuremonitor/1-azure-monitor-response-avg.json")
So(err, ShouldBeNil)
So(data.Interval, ShouldEqual, "PT1M")
func makeDates(startDate time.Time, count int, interval time.Duration) (times []time.Time) {
for i := 0; i < count; i++ {
times = append(times, startDate.Add(interval*time.Duration(i)))
}
return
}
res := &tsdb.QueryResult{Meta: simplejson.New(), RefId: "A"}
query := &AzureMonitorQuery{
func TestAzureMonitorParseResponse(t *testing.T) {
tests := []struct {
name string
responseFile string
mockQuery *AzureMonitorQuery
expectedFrames data.Frames
queryIntervalMS int64
}{
{
name: "average aggregate time series response",
responseFile: "1-azure-monitor-response-avg.json",
mockQuery: &AzureMonitorQuery{
UrlComponents: map[string]string{
"resourceName": "grafana",
},
Params: url.Values{
"aggregation": {"Average"},
},
}
err = datasource.parseResponse(res, data, query)
So(err, ShouldBeNil)
So(len(res.Series), ShouldEqual, 1)
So(res.Series[0].Name, ShouldEqual, "grafana.Percentage CPU")
So(len(res.Series[0].Points), ShouldEqual, 5)
So(res.Series[0].Points[0][0].Float64, ShouldEqual, 2.0875)
So(res.Series[0].Points[0][1].Float64, ShouldEqual, int64(1549620780000))
So(res.Series[0].Points[1][0].Float64, ShouldEqual, 2.1525)
So(res.Series[0].Points[1][1].Float64, ShouldEqual, int64(1549620840000))
So(res.Series[0].Points[2][0].Float64, ShouldEqual, 2.155)
So(res.Series[0].Points[2][1].Float64, ShouldEqual, int64(1549620900000))
So(res.Series[0].Points[3][0].Float64, ShouldEqual, 3.6925)
So(res.Series[0].Points[3][1].Float64, ShouldEqual, int64(1549620960000))
So(res.Series[0].Points[4][0].Float64, ShouldEqual, 2.44)
So(res.Series[0].Points[4][1].Float64, ShouldEqual, int64(1549621020000))
})
Convey("when data from query aggregated as total to one time series", func() {
data, err := loadTestFile("azuremonitor/2-azure-monitor-response-total.json")
So(err, ShouldBeNil)
res := &tsdb.QueryResult{Meta: simplejson.New(), RefId: "A"}
query := &AzureMonitorQuery{
},
expectedFrames: data.Frames{
data.NewFrame("",
data.NewField("", nil,
makeDates(time.Date(2019, 2, 8, 10, 13, 0, 0, time.UTC), 5, time.Minute)),
data.NewField("grafana.Percentage CPU", nil, []float64{
2.0875, 2.1525, 2.155, 3.6925, 2.44,
}).SetConfig(&data.FieldConfig{Unit: "Percent"})),
},
},
{
name: "total aggregate time series response",
responseFile: "2-azure-monitor-response-total.json",
mockQuery: &AzureMonitorQuery{
UrlComponents: map[string]string{
"resourceName": "grafana",
},
Params: url.Values{
"aggregation": {"Total"},
},
}
err = datasource.parseResponse(res, data, query)
So(err, ShouldBeNil)
So(res.Series[0].Points[0][0].Float64, ShouldEqual, 8.26)
So(res.Series[0].Points[0][1].Float64, ShouldEqual, int64(1549718940000))
})
Convey("when data from query aggregated as maximum to one time series", func() {
data, err := loadTestFile("azuremonitor/3-azure-monitor-response-maximum.json")
So(err, ShouldBeNil)
res := &tsdb.QueryResult{Meta: simplejson.New(), RefId: "A"}
query := &AzureMonitorQuery{
},
expectedFrames: data.Frames{
data.NewFrame("",
data.NewField("", nil,
makeDates(time.Date(2019, 2, 9, 13, 29, 0, 0, time.UTC), 5, time.Minute)),
data.NewField("grafana.Percentage CPU", nil, []float64{
8.26, 8.7, 14.82, 10.07, 8.52,
}).SetConfig(&data.FieldConfig{Unit: "Percent"})),
},
},
{
name: "maximum aggregate time series response",
responseFile: "3-azure-monitor-response-maximum.json",
mockQuery: &AzureMonitorQuery{
UrlComponents: map[string]string{
"resourceName": "grafana",
},
Params: url.Values{
"aggregation": {"Maximum"},
},
}
err = datasource.parseResponse(res, data, query)
So(err, ShouldBeNil)
So(res.Series[0].Points[0][0].Float64, ShouldEqual, 3.07)
So(res.Series[0].Points[0][1].Float64, ShouldEqual, int64(1549722360000))
})
Convey("when data from query aggregated as minimum to one time series", func() {
data, err := loadTestFile("azuremonitor/4-azure-monitor-response-minimum.json")
So(err, ShouldBeNil)
res := &tsdb.QueryResult{Meta: simplejson.New(), RefId: "A"}
query := &AzureMonitorQuery{
},
expectedFrames: data.Frames{
data.NewFrame("",
data.NewField("", nil,
makeDates(time.Date(2019, 2, 9, 14, 26, 0, 0, time.UTC), 5, time.Minute)),
data.NewField("grafana.Percentage CPU", nil, []float64{
3.07, 2.92, 2.87, 2.27, 2.52,
}).SetConfig(&data.FieldConfig{Unit: "Percent"})),
},
},
{
name: "minimum aggregate time series response",
responseFile: "4-azure-monitor-response-minimum.json",
mockQuery: &AzureMonitorQuery{
UrlComponents: map[string]string{
"resourceName": "grafana",
},
Params: url.Values{
"aggregation": {"Minimum"},
},
}
err = datasource.parseResponse(res, data, query)
So(err, ShouldBeNil)
So(res.Series[0].Points[0][0].Float64, ShouldEqual, 1.51)
So(res.Series[0].Points[0][1].Float64, ShouldEqual, int64(1549723380000))
})
Convey("when data from query aggregated as Count to one time series", func() {
data, err := loadTestFile("azuremonitor/5-azure-monitor-response-count.json")
So(err, ShouldBeNil)
res := &tsdb.QueryResult{Meta: simplejson.New(), RefId: "A"}
query := &AzureMonitorQuery{
},
expectedFrames: data.Frames{
data.NewFrame("",
data.NewField("", nil,
makeDates(time.Date(2019, 2, 9, 14, 43, 0, 0, time.UTC), 5, time.Minute)),
data.NewField("grafana.Percentage CPU", nil, []float64{
1.51, 2.38, 1.69, 2.27, 1.96,
}).SetConfig(&data.FieldConfig{Unit: "Percent"})),
},
},
{
name: "count aggregate time series response",
responseFile: "5-azure-monitor-response-count.json",
mockQuery: &AzureMonitorQuery{
UrlComponents: map[string]string{
"resourceName": "grafana",
},
Params: url.Values{
"aggregation": {"Count"},
},
}
err = datasource.parseResponse(res, data, query)
So(err, ShouldBeNil)
So(res.Series[0].Points[0][0].Float64, ShouldEqual, 4)
So(res.Series[0].Points[0][1].Float64, ShouldEqual, int64(1549723440000))
})
Convey("when data from query aggregated as total and has dimension filter", func() {
data, err := loadTestFile("azuremonitor/6-azure-monitor-response-multi-dimension.json")
So(err, ShouldBeNil)
res := &tsdb.QueryResult{Meta: simplejson.New(), RefId: "A"}
query := &AzureMonitorQuery{
},
expectedFrames: data.Frames{
data.NewFrame("",
data.NewField("", nil,
makeDates(time.Date(2019, 2, 9, 14, 44, 0, 0, time.UTC), 5, time.Minute)),
data.NewField("grafana.Percentage CPU", nil, []float64{
4, 4, 4, 4, 4,
}).SetConfig(&data.FieldConfig{Unit: "Percent"})),
},
},
{
name: "multi dimension time series response",
responseFile: "6-azure-monitor-response-multi-dimension.json",
mockQuery: &AzureMonitorQuery{
UrlComponents: map[string]string{
"resourceName": "grafana",
},
Params: url.Values{
"aggregation": {"Average"},
},
}
err = datasource.parseResponse(res, data, query)
So(err, ShouldBeNil)
So(len(res.Series), ShouldEqual, 3)
So(res.Series[0].Name, ShouldEqual, "grafana{blobtype=PageBlob}.Blob Count")
So(res.Series[0].Points[0][0].Float64, ShouldEqual, 3)
So(res.Series[1].Name, ShouldEqual, "grafana{blobtype=BlockBlob}.Blob Count")
So(res.Series[1].Points[0][0].Float64, ShouldEqual, 1)
So(res.Series[2].Name, ShouldEqual, "grafana{blobtype=Azure Data Lake Storage}.Blob Count")
So(res.Series[2].Points[0][0].Float64, ShouldEqual, 0)
})
Convey("when data from query has alias patterns", func() {
data, err := loadTestFile("azuremonitor/2-azure-monitor-response-total.json")
So(err, ShouldBeNil)
res := &tsdb.QueryResult{Meta: simplejson.New(), RefId: "A"}
query := &AzureMonitorQuery{
},
// Regarding multi-dimensional response:
// - It seems they all share the same time index, so maybe can be a wide frame.
// - Due to the type for the Azure monitor response, nulls currently become 0.
// - blogtype=X should maybe become labels.
expectedFrames: data.Frames{
data.NewFrame("",
data.NewField("", nil,
makeDates(time.Date(2019, 2, 9, 15, 21, 0, 0, time.UTC), 6, time.Hour)),
data.NewField("grafana{blobtype=PageBlob}.Blob Count", nil, []float64{
3, 3, 3, 3, 3, 0,
}).SetConfig(&data.FieldConfig{Unit: "Count"})),
data.NewFrame("",
data.NewField("", nil,
makeDates(time.Date(2019, 2, 9, 15, 21, 0, 0, time.UTC), 6, time.Hour)),
data.NewField("grafana{blobtype=BlockBlob}.Blob Count", nil, []float64{
1, 1, 1, 1, 1, 0,
}).SetConfig(&data.FieldConfig{Unit: "Count"})),
data.NewFrame("",
data.NewField("", nil,
makeDates(time.Date(2019, 2, 9, 15, 21, 0, 0, time.UTC), 6, time.Hour)),
data.NewField("grafana{blobtype=Azure Data Lake Storage}.Blob Count", nil, []float64{
0, 0, 0, 0, 0, 0,
}).SetConfig(&data.FieldConfig{Unit: "Count"})),
},
},
{
name: "with alias patterns in the query",
responseFile: "2-azure-monitor-response-total.json",
mockQuery: &AzureMonitorQuery{
Alias: "custom {{resourcegroup}} {{namespace}} {{resourceName}} {{metric}}",
UrlComponents: map[string]string{
"resourceName": "grafana",
......@@ -324,19 +313,20 @@ func TestAzureMonitorDatasource(t *testing.T) {
Params: url.Values{
"aggregation": {"Total"},
},
}
err = datasource.parseResponse(res, data, query)
So(err, ShouldBeNil)
So(res.Series[0].Name, ShouldEqual, "custom grafanastaging Microsoft.Compute/virtualMachines grafana Percentage CPU")
})
Convey("when data has dimension filters and alias patterns", func() {
data, err := loadTestFile("azuremonitor/6-azure-monitor-response-multi-dimension.json")
So(err, ShouldBeNil)
res := &tsdb.QueryResult{Meta: simplejson.New(), RefId: "A"}
query := &AzureMonitorQuery{
},
expectedFrames: data.Frames{
data.NewFrame("",
data.NewField("", nil,
makeDates(time.Date(2019, 2, 9, 13, 29, 0, 0, time.UTC), 5, time.Minute)),
data.NewField("custom grafanastaging Microsoft.Compute/virtualMachines grafana Percentage CPU", nil, []float64{
8.26, 8.7, 14.82, 10.07, 8.52,
}).SetConfig(&data.FieldConfig{Unit: "Percent"})),
},
},
{
name: "multi dimension with alias",
responseFile: "6-azure-monitor-response-multi-dimension.json",
mockQuery: &AzureMonitorQuery{
Alias: "{{dimensionname}}={{DimensionValue}}",
UrlComponents: map[string]string{
"resourceName": "grafana",
......@@ -344,18 +334,53 @@ func TestAzureMonitorDatasource(t *testing.T) {
Params: url.Values{
"aggregation": {"Average"},
},
},
expectedFrames: data.Frames{
data.NewFrame("",
data.NewField("", nil,
makeDates(time.Date(2019, 2, 9, 15, 21, 0, 0, time.UTC), 6, time.Hour)),
data.NewField("blobtype=PageBlob", nil, []float64{
3, 3, 3, 3, 3, 0,
}).SetConfig(&data.FieldConfig{Unit: "Count"})),
data.NewFrame("",
data.NewField("", nil,
makeDates(time.Date(2019, 2, 9, 15, 21, 0, 0, time.UTC), 6, time.Hour)),
data.NewField("blobtype=BlockBlob", nil, []float64{
1, 1, 1, 1, 1, 0,
}).SetConfig(&data.FieldConfig{Unit: "Count"})),
data.NewFrame("",
data.NewField("", nil,
makeDates(time.Date(2019, 2, 9, 15, 21, 0, 0, time.UTC), 6, time.Hour)),
data.NewField("blobtype=Azure Data Lake Storage", nil, []float64{
0, 0, 0, 0, 0, 0,
}).SetConfig(&data.FieldConfig{Unit: "Count"})),
},
},
}
err = datasource.parseResponse(res, data, query)
So(err, ShouldBeNil)
So(res.Series[0].Name, ShouldEqual, "blobtype=PageBlob")
So(res.Series[1].Name, ShouldEqual, "blobtype=BlockBlob")
So(res.Series[2].Name, ShouldEqual, "blobtype=Azure Data Lake Storage")
})
datasource := &AzureMonitorDatasource{}
for _, tt := range tests {
t.Run(tt.name, func(t *testing.T) {
azData, err := loadTestFile("azuremonitor/" + tt.responseFile)
require.NoError(t, err)
res := &tsdb.QueryResult{Meta: simplejson.New(), RefId: "A"}
err = datasource.parseResponse(res, azData, tt.mockQuery)
require.NoError(t, err)
frames, err := data.UnmarshalArrowFrames(res.Dataframes)
require.NoError(t, err)
if diff := cmp.Diff(tt.expectedFrames, frames, data.FrameTestCompareOptions()...); diff != "" {
t.Errorf("Result mismatch (-want +got):\n%s", diff)
}
})
}
}
Convey("Find closest allowed interval for auto time grain", func() {
intervals := map[string]int64{
func TestFindClosestAllowIntervalMS(t *testing.T) {
humanIntervalToMS := map[string]int64{
"3m": 180000,
"5m": 300000,
"10m": 600000,
......@@ -363,30 +388,53 @@ func TestAzureMonitorDatasource(t *testing.T) {
"1d": 86400000,
"2d": 172800000,
}
closest := findClosestAllowedIntervalMS(intervals["3m"], []int64{})
So(closest, ShouldEqual, intervals["5m"])
closest = findClosestAllowedIntervalMS(intervals["10m"], []int64{})
So(closest, ShouldEqual, intervals["15m"])
closest = findClosestAllowedIntervalMS(intervals["2d"], []int64{})
So(closest, ShouldEqual, intervals["1d"])
closest = findClosestAllowedIntervalMS(intervals["3m"], []int64{intervals["1d"]})
So(closest, ShouldEqual, intervals["1d"])
})
tests := []struct {
name string
allowedTimeGrains []int64 // Note: Uses defaults when empty list
inputInterval int64
expectedInterval int64
}{
{
name: "closest to 3m is 5m",
allowedTimeGrains: []int64{},
inputInterval: humanIntervalToMS["3m"],
expectedInterval: humanIntervalToMS["5m"],
},
{
name: "closest to 10m is 15m",
allowedTimeGrains: []int64{},
inputInterval: humanIntervalToMS["10m"],
expectedInterval: humanIntervalToMS["15m"],
},
{
name: "closest to 2d is 1d",
allowedTimeGrains: []int64{},
inputInterval: humanIntervalToMS["2d"],
expectedInterval: humanIntervalToMS["1d"],
},
{
name: "closest to 3m is 1d when 1d is only allowed interval",
allowedTimeGrains: []int64{humanIntervalToMS["1d"]},
inputInterval: humanIntervalToMS["2d"],
expectedInterval: humanIntervalToMS["1d"],
},
}
for _, tt := range tests {
t.Run(tt.name, func(t *testing.T) {
interval := findClosestAllowedIntervalMS(tt.inputInterval, tt.allowedTimeGrains)
require.Equal(t, tt.expectedInterval, interval)
})
}
}
func loadTestFile(name string) (AzureMonitorResponse, error) {
var data AzureMonitorResponse
var azData AzureMonitorResponse
path := filepath.Join("testdata", name)
jsonBody, err := ioutil.ReadFile(path)
if err != nil {
return data, err
return azData, err
}
err = json.Unmarshal(jsonBody, &data)
return data, err
err = json.Unmarshal(jsonBody, &azData)
return azData, err
}
public/app/features/dashboard/state/runRequest.ts
......@@ -21,6 +21,7 @@ import {
import { toDataQueryError } from '@grafana/runtime';
import { emitDataRequestEvent } from './analyticsProcessor';
import { ExpressionDatasourceID, expressionDatasource } from 'app/features/expressions/ExpressionDatasource';
import { ExpressionQuery } from 'app/features/expressions/types';
type MapOfResponsePackets = { [str: string]: DataQueryResponse };
......@@ -145,7 +146,7 @@ export function callQueryMethod(datasource: DataSourceApi, request: DataQueryReq
// If any query has an expression, use the expression endpoint
for (const target of request.targets) {
if (target.datasource === ExpressionDatasourceID) {
return expressionDatasource.query(request);
return expressionDatasource.query(request as DataQueryRequest<ExpressionQuery>);
}
}
......
public/app/plugins/datasource/grafana-azure-monitor-datasource/azure_monitor/azure_monitor_datasource.test.ts
import AzureMonitorDatasource from '../datasource';
import { TemplateSrv } from 'app/features/templating/template_srv';
import { toUtc, DataFrame, getFrameDisplayName } from '@grafana/data';
import { DataSourceInstanceSettings } from '@grafana/data';
import { backendSrv } from 'app/core/services/backend_srv'; // will use the version in __mocks__
import { AzureDataSourceJsonData } from '../types';
const templateSrv = new TemplateSrv();
jest.mock('@grafana/runtime', () => ({
...jest.requireActual('@grafana/runtime'),
getBackendSrv: () => backendSrv,
getTemplateSrv: () => templateSrv,
}));
interface TestContext {
instanceSettings: DataSourceInstanceSettings<AzureDataSourceJsonData>;
ds: AzureMonitorDatasource;
}
describe('AzureMonitorDatasource', () => {
const ctx: any = {
templateSrv: new TemplateSrv(),
};
const ctx: TestContext = {} as TestContext;
const datasourceRequestMock = jest.spyOn(backendSrv, 'datasourceRequest');
beforeEach(() => {
jest.clearAllMocks();
ctx.instanceSettings = {
ctx.instanceSettings = ({
name: 'test',
url: 'http://azuremonitor.com',
jsonData: { subscriptionId: '9935389e-9122-4ef9-95f9-1513dd24753f' },
cloudName: 'azuremonitor',
};
ctx.ds = new AzureMonitorDatasource(ctx.instanceSettings, ctx.templateSrv);
} as unknown) as DataSourceInstanceSettings<AzureDataSourceJsonData>;
ctx.ds = new AzureMonitorDatasource(ctx.instanceSettings, templateSrv);
});
describe('When performing testDatasource', () => {
......@@ -78,74 +85,6 @@ describe('AzureMonitorDatasource', () => {
});
});
describe('When performing query', () => {
const options = {
range: {
from: toUtc('2017-08-22T20:00:00Z'),
to: toUtc('2017-08-22T23:59:00Z'),
},
targets: [
{
apiVersion: '2018-01-01',
refId: 'A',
queryType: 'Azure Monitor',
azureMonitor: {
resourceGroup: 'testRG',
resourceName: 'testRN',
metricDefinition: 'Microsoft.Compute/virtualMachines',
metricNamespace: 'default',
metricName: 'Percentage CPU',
timeGrain: 'PT1H',
alias: '{{metric}}',
},
},
],
};
const response: any = {
results: {
A: {
refId: 'A',
meta: {
rawQuery:
'aggregation=Average&api-version=2018-01-01&interval=PT1M' +
'&metricnames=Percentage+CPU&timespan=2019-05-19T15%3A11%3A37Z%2F2019-05-19T21%3A11%3A37Z',
unit: 'Percent',
},
series: [
{
name: 'Percentage CPU',
points: [
[2.2075, 1558278660000],
[2.29, 1558278720000],
],
},
],
tables: null,
},
},
};
beforeEach(() => {
datasourceRequestMock.mockImplementation((options: { url: string }) => {
expect(options.url).toContain('/api/tsdb/query');
return Promise.resolve({ 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(getFrameDisplayName(data)).toEqual('Percentage CPU');
expect(data.fields[0].values.get(0)).toEqual(1558278660000);
expect(data.fields[1].values.get(0)).toEqual(2.2075);
expect(data.fields[0].values.get(1)).toEqual(1558278720000);
expect(data.fields[1].values.get(1)).toEqual(2.29);
});
});
});
describe('When performing metricFindQuery', () => {
describe('with a subscriptions query', () => {
const response = {
......@@ -626,7 +565,7 @@ describe('AzureMonitorDatasource', () => {
});
it('should return list of Resource Groups', () => {
return ctx.ds.getResourceGroups().then((results: Array<{ text: string; value: string }>) => {
return ctx.ds.getResourceGroups('subscriptionId').then((results: Array<{ text: string; value: string }>) => {
expect(results.length).toEqual(2);
expect(results[0].text).toEqual('grp1');
expect(results[0].value).toEqual('grp1');
......
public/app/plugins/datasource/grafana-azure-monitor-datasource/azure_monitor/azure_monitor_datasource.ts
import _ from 'lodash';
import { filter, startsWith } from 'lodash';
import UrlBuilder from './url_builder';
import ResponseParser from './response_parser';
import SupportedNamespaces from './supported_namespaces';
......@@ -9,31 +9,25 @@ import {
AzureMonitorMetricDefinitionsResponse,
AzureMonitorResourceGroupsResponse,
} from '../types';
import { DataQueryRequest, DataQueryResponseData, DataSourceInstanceSettings } from '@grafana/data';
import { DataSourceInstanceSettings, ScopedVars } from '@grafana/data';
import { getBackendSrv, DataSourceWithBackend, getTemplateSrv } from '@grafana/runtime';
import { TimeSeries, toDataFrame } from '@grafana/data';
import { TemplateSrv } from 'app/features/templating/template_srv';
import { getBackendSrv } from '@grafana/runtime';
const defaultDropdownValue = 'select';
export default class AzureMonitorDatasource {
export default class AzureMonitorDatasource extends DataSourceWithBackend<AzureMonitorQuery, AzureDataSourceJsonData> {
apiVersion = '2018-01-01';
apiPreviewVersion = '2017-12-01-preview';
id: number;
subscriptionId: string;
baseUrl: string;
resourceGroup: string;
resourceName: string;
url: string;
defaultDropdownValue = 'select';
cloudName: string;
supportedMetricNamespaces: string[] = [];
/** @ngInject */
constructor(
private instanceSettings: DataSourceInstanceSettings<AzureDataSourceJsonData>,
private templateSrv: TemplateSrv
) {
this.id = instanceSettings.id;
constructor(private instanceSettings: DataSourceInstanceSettings<AzureDataSourceJsonData>) {
super(instanceSettings);
this.subscriptionId = instanceSettings.jsonData.subscriptionId;
this.cloudName = instanceSettings.jsonData.cloudName || 'azuremonitor';
this.baseUrl = `/${this.cloudName}/subscriptions`;
......@@ -46,20 +40,21 @@ export default class AzureMonitorDatasource {
return !!this.subscriptionId && this.subscriptionId.length > 0;
}
async query(options: DataQueryRequest<AzureMonitorQuery>): Promise<DataQueryResponseData[]> {
const queries = _.filter(options.targets, item => {
filterQuery(item: AzureMonitorQuery): boolean {
return (
item.hide !== true &&
item.azureMonitor.resourceGroup &&
item.azureMonitor.resourceGroup !== this.defaultDropdownValue &&
item.azureMonitor.resourceGroup !== defaultDropdownValue &&
item.azureMonitor.resourceName &&
item.azureMonitor.resourceName !== this.defaultDropdownValue &&
item.azureMonitor.resourceName !== defaultDropdownValue &&
item.azureMonitor.metricDefinition &&
item.azureMonitor.metricDefinition !== this.defaultDropdownValue &&
item.azureMonitor.metricDefinition !== defaultDropdownValue &&
item.azureMonitor.metricName &&
item.azureMonitor.metricName !== this.defaultDropdownValue
item.azureMonitor.metricName !== defaultDropdownValue
);
}).map(target => {
}
applyTemplateVariables(target: AzureMonitorQuery, scopedVars: ScopedVars): Record<string, any> {
const item = target.azureMonitor;
// fix for timeGrainUnit which is a deprecated/removed field name
......@@ -67,80 +62,42 @@ export default class AzureMonitorDatasource {
item.timeGrain = TimegrainConverter.createISO8601Duration(item.timeGrain, item.timeGrainUnit);
}
const subscriptionId = this.templateSrv.replace(target.subscription || this.subscriptionId, options.scopedVars);
const resourceGroup = this.templateSrv.replace(item.resourceGroup, options.scopedVars);
const resourceName = this.templateSrv.replace(item.resourceName, options.scopedVars);
const metricNamespace = this.templateSrv.replace(item.metricNamespace, options.scopedVars);
const metricDefinition = this.templateSrv.replace(item.metricDefinition, options.scopedVars);
const timeGrain = this.templateSrv.replace((item.timeGrain || '').toString(), options.scopedVars);
const aggregation = this.templateSrv.replace(item.aggregation, options.scopedVars);
const top = this.templateSrv.replace(item.top || '', options.scopedVars);
const templateSrv = getTemplateSrv();
const subscriptionId = templateSrv.replace(target.subscription || this.subscriptionId, scopedVars);
const resourceGroup = templateSrv.replace(item.resourceGroup, scopedVars);
const resourceName = templateSrv.replace(item.resourceName, scopedVars);
const metricNamespace = templateSrv.replace(item.metricNamespace, scopedVars);
const metricDefinition = templateSrv.replace(item.metricDefinition, scopedVars);
const timeGrain = templateSrv.replace((item.timeGrain || '').toString(), scopedVars);
const aggregation = templateSrv.replace(item.aggregation, scopedVars);
const top = templateSrv.replace(item.top || '', scopedVars);
return {
refId: target.refId,
intervalMs: options.intervalMs,
datasourceId: this.id,
subscription: subscriptionId,
queryType: 'Azure Monitor',
type: 'timeSeriesQuery',
raw: false,
azureMonitor: {
resourceGroup: resourceGroup,
resourceName: resourceName,
metricDefinition: metricDefinition,
timeGrain: timeGrain,
resourceGroup,
resourceName,
metricDefinition,
timeGrain,
allowedTimeGrainsMs: item.allowedTimeGrainsMs,
metricName: this.templateSrv.replace(item.metricName, options.scopedVars),
metricName: templateSrv.replace(item.metricName, scopedVars),
metricNamespace:
metricNamespace && metricNamespace !== this.defaultDropdownValue ? metricNamespace : metricDefinition,
metricNamespace && metricNamespace !== defaultDropdownValue ? metricNamespace : metricDefinition,
aggregation: aggregation,
dimension: this.templateSrv.replace(item.dimension, options.scopedVars),
dimension: templateSrv.replace(item.dimension, scopedVars),
top: top || '10',
dimensionFilter: this.templateSrv.replace(item.dimensionFilter, options.scopedVars),
dimensionFilter: templateSrv.replace(item.dimensionFilter, scopedVars),
alias: item.alias,
format: target.format,
},
};
});
if (!queries || queries.length === 0) {
return Promise.resolve([]);
}
const { data } = await getBackendSrv().datasourceRequest({
url: '/api/tsdb/query',
method: 'POST',
data: {
from: options.range.from.valueOf().toString(),
to: options.range.to.valueOf().toString(),
queries,
},
});
const result: DataQueryResponseData[] = [];
if (data.results) {
Object['values'](data.results).forEach((queryRes: any) => {
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([]);
}
annotationQuery(options: any) {}
metricFindQuery(query: string) {
const subscriptionsQuery = query.match(/^Subscriptions\(\)/i);
if (subscriptionsQuery) {
......@@ -234,7 +191,7 @@ export default class AzureMonitorDatasource {
}
toVariable(metric: string) {
return this.templateSrv.replace((metric || '').trim());
return getTemplateSrv().replace((metric || '').trim());
}
getSubscriptions(route?: string) {
......@@ -258,7 +215,7 @@ export default class AzureMonitorDatasource {
return ResponseParser.parseResponseValues(result, 'type', 'type');
})
.then((result: any) => {
return _.filter(result, t => {
return filter(result, t => {
for (let i = 0; i < this.supportedMetricNamespaces.length; i++) {
if (t.value.toLowerCase() === this.supportedMetricNamespaces[i].toLowerCase()) {
return true;
......@@ -304,7 +261,7 @@ export default class AzureMonitorDatasource {
const url = `${this.baseUrl}/${subscriptionId}/resourceGroups/${resourceGroup}/resources?api-version=${this.apiVersion}`;
return this.doRequest(url).then((result: any) => {
if (!_.startsWith(metricDefinition, 'Microsoft.Storage/storageAccounts/')) {
if (!startsWith(metricDefinition, 'Microsoft.Storage/storageAccounts/')) {
return ResponseParser.parseResourceNames(result, metricDefinition);
}
......@@ -378,19 +335,19 @@ export default class AzureMonitorDatasource {
});
}
testDatasource() {
testDatasource(): Promise<any> {
if (!this.isValidConfigField(this.instanceSettings.jsonData.tenantId)) {
return {
return Promise.resolve({
status: 'error',
message: 'The Tenant Id field is required.',
};
});
}
if (!this.isValidConfigField(this.instanceSettings.jsonData.clientId)) {
return {
return Promise.resolve({
status: 'error',
message: 'The Client Id field is required.',
};
});
}
const url = `/${this.cloudName}/subscriptions?api-version=2019-03-01`;
......
public/app/plugins/datasource/grafana-azure-monitor-datasource/datasource.ts
......@@ -3,8 +3,15 @@ import AzureMonitorDatasource from './azure_monitor/azure_monitor_datasource';
import AppInsightsDatasource from './app_insights/app_insights_datasource';
import AzureLogAnalyticsDatasource from './azure_log_analytics/azure_log_analytics_datasource';
import { AzureMonitorQuery, AzureDataSourceJsonData } from './types';
import { DataSourceApi, DataQueryRequest, DataSourceInstanceSettings } from '@grafana/data';
import {
DataSourceApi,
DataQueryRequest,
DataSourceInstanceSettings,
DataQueryResponse,
DataQueryResponseData,
} from '@grafana/data';
import { TemplateSrv } from 'app/features/templating/template_srv';
import { Observable } from 'rxjs';
export default class Datasource extends DataSourceApi<AzureMonitorQuery, AzureDataSourceJsonData> {
azureMonitorDatasource: AzureMonitorDatasource;
......@@ -14,13 +21,12 @@ export default class Datasource extends DataSourceApi<AzureMonitorQuery, AzureDa
/** @ngInject */
constructor(instanceSettings: DataSourceInstanceSettings<AzureDataSourceJsonData>, private templateSrv: TemplateSrv) {
super(instanceSettings);
this.azureMonitorDatasource = new AzureMonitorDatasource(instanceSettings, this.templateSrv);
this.azureMonitorDatasource = new AzureMonitorDatasource(instanceSettings);
this.appInsightsDatasource = new AppInsightsDatasource(instanceSettings, this.templateSrv);
this.azureLogAnalyticsDatasource = new AzureLogAnalyticsDatasource(instanceSettings, this.templateSrv);
}
async query(options: DataQueryRequest<AzureMonitorQuery>) {
query(options: DataQueryRequest<AzureMonitorQuery>): Promise<DataQueryResponse> | Observable<DataQueryResponseData> {
const promises: any[] = [];
const azureMonitorOptions = _.cloneDeep(options);
const appInsightsOptions = _.cloneDeep(options);
......@@ -30,13 +36,6 @@ export default class Datasource extends DataSourceApi<AzureMonitorQuery, AzureDa
appInsightsOptions.targets = _.filter(appInsightsOptions.targets, ['queryType', 'Application Insights']);
azureLogAnalyticsOptions.targets = _.filter(azureLogAnalyticsOptions.targets, ['queryType', 'Azure Log Analytics']);
if (azureMonitorOptions.targets.length > 0) {
const amPromise = this.azureMonitorDatasource.query(azureMonitorOptions);
if (amPromise) {
promises.push(amPromise);
}
}
if (appInsightsOptions.targets.length > 0) {
const aiPromise = this.appInsightsDatasource.query(appInsightsOptions);
if (aiPromise) {
......@@ -51,6 +50,16 @@ export default class Datasource extends DataSourceApi<AzureMonitorQuery, AzureDa
}
}
if (azureMonitorOptions.targets.length > 0) {
const obs = this.azureMonitorDatasource.query(azureMonitorOptions);
if (!promises.length) {
return obs; // return the observable directly
}
// NOTE: this only includes the data!
// When all three query types are ready to be observale, they should all use observable
promises.push(obs.toPromise().then(r => r.data));
}
if (promises.length === 0) {
return Promise.resolve({ data: [] });
}
......
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