Daniel Lee
a6a939cfd3
* fix: azuremonitor adds multi-sub support to alerting
* fix: AzureMonitor missing parameter in metadata func
getMetricMetadata function when called in the query ctrl
was missing a parameter for Subscription Id.
Also, made some tweaks to what happens when a chained
dropdown is changed to not reset all the fields that
are dependent on it.
(cherry picked from commit fa9ffe38d2)
272 lines
9.4 KiB
Go
272 lines
9.4 KiB
Go
package azuremonitor
|
|
|
|
import (
|
|
"encoding/json"
|
|
"fmt"
|
|
"io/ioutil"
|
|
"net/url"
|
|
"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 TestAzureMonitorDatasource(t *testing.T) {
|
|
Convey("AzureMonitorDatasource", t, func() {
|
|
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{
|
|
{
|
|
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{}{
|
|
"timeGrain": "PT1M",
|
|
"aggregation": "Average",
|
|
"resourceGroup": "grafanastaging",
|
|
"resourceName": "grafana",
|
|
"metricDefinition": "Microsoft.Compute/virtualMachines",
|
|
"metricName": "Percentage CPU",
|
|
"alias": "testalias",
|
|
"queryType": "Azure Monitor",
|
|
},
|
|
}),
|
|
RefId: "A",
|
|
},
|
|
},
|
|
}
|
|
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×pan=2018-03-15T13%3A00%3A00Z%2F2018-03-15T13%3A34%3A00Z")
|
|
So(len(queries[0].Params), ShouldEqual, 5)
|
|
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 dimension filter", func() {
|
|
tsdbQuery.Queries[0].Model = simplejson.NewFromAny(map[string]interface{}{
|
|
"azureMonitor": map[string]interface{}{
|
|
"timeGrain": "PT1M",
|
|
"aggregation": "Average",
|
|
"resourceGroup": "grafanastaging",
|
|
"resourceName": "grafana",
|
|
"metricDefinition": "Microsoft.Compute/virtualMachines",
|
|
"metricName": "Percentage CPU",
|
|
"alias": "testalias",
|
|
"queryType": "Azure Monitor",
|
|
"dimension": "blob",
|
|
"dimensionFilter": "*",
|
|
},
|
|
})
|
|
|
|
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×pan=2018-03-15T13%3A00%3A00Z%2F2018-03-15T13%3A34%3A00Z")
|
|
|
|
})
|
|
})
|
|
|
|
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")
|
|
So(err, ShouldBeNil)
|
|
So(data.Interval, ShouldEqual, "PT1M")
|
|
|
|
res := &tsdb.QueryResult{Meta: simplejson.New(), RefId: "A"}
|
|
query := &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("./test-data/2-azure-monitor-response-total.json")
|
|
So(err, ShouldBeNil)
|
|
|
|
res := &tsdb.QueryResult{Meta: simplejson.New(), RefId: "A"}
|
|
query := &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("./test-data/3-azure-monitor-response-maximum.json")
|
|
So(err, ShouldBeNil)
|
|
|
|
res := &tsdb.QueryResult{Meta: simplejson.New(), RefId: "A"}
|
|
query := &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("./test-data/4-azure-monitor-response-minimum.json")
|
|
So(err, ShouldBeNil)
|
|
|
|
res := &tsdb.QueryResult{Meta: simplejson.New(), RefId: "A"}
|
|
query := &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("./test-data/5-azure-monitor-response-count.json")
|
|
So(err, ShouldBeNil)
|
|
|
|
res := &tsdb.QueryResult{Meta: simplejson.New(), RefId: "A"}
|
|
query := &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("./test-data/6-azure-monitor-response-multi-dimension.json")
|
|
So(err, ShouldBeNil)
|
|
|
|
res := &tsdb.QueryResult{Meta: simplejson.New(), RefId: "A"}
|
|
query := &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("Find closest allowed interval for auto time grain", func() {
|
|
intervals := map[string]int64{
|
|
"3m": 180000,
|
|
"5m": 300000,
|
|
"10m": 600000,
|
|
"15m": 900000,
|
|
"1d": 86400000,
|
|
"2d": 172800000,
|
|
}
|
|
|
|
closest := datasource.findClosestAllowedIntervalMS(intervals["3m"])
|
|
So(closest, ShouldEqual, intervals["5m"])
|
|
|
|
closest = datasource.findClosestAllowedIntervalMS(intervals["10m"])
|
|
So(closest, ShouldEqual, intervals["15m"])
|
|
|
|
closest = datasource.findClosestAllowedIntervalMS(intervals["2d"])
|
|
So(closest, ShouldEqual, intervals["1d"])
|
|
})
|
|
})
|
|
}
|
|
|
|
func loadTestFile(path string) (AzureMonitorResponse, error) {
|
|
var data AzureMonitorResponse
|
|
|
|
jsonBody, err := ioutil.ReadFile(path)
|
|
if err != nil {
|
|
return data, err
|
|
}
|
|
err = json.Unmarshal(jsonBody, &data)
|
|
return data, err
|
|
}
|