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)
This commit is contained in:
Chad Nedzlek
Daniel Lee
@@ -0,0 +1,592 @@
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package azuremonitor
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import (
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"context"
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"encoding/json"
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"errors"
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"fmt"
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"github.com/grafana/grafana/pkg/api/pluginproxy"
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"github.com/grafana/grafana/pkg/components/null"
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"github.com/grafana/grafana/pkg/components/simplejson"
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"github.com/grafana/grafana/pkg/models"
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"github.com/grafana/grafana/pkg/plugins"
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"github.com/grafana/grafana/pkg/setting"
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"github.com/grafana/grafana/pkg/tsdb"
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"github.com/opentracing/opentracing-go"
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"golang.org/x/net/context/ctxhttp"
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"io/ioutil"
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"net/http"
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"net/url"
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"path"
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"strings"
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"time"
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)
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// ApplicationInsightsDatasource calls the application insights query API's
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type ApplicationInsightsDatasource struct {
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httpClient *http.Client
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dsInfo *models.DataSource
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}
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type ApplicationInsightsQuery struct {
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RefID string
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IsRaw bool
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// Text based raw query options
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ApiURL string
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Params url.Values
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Alias string
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Target string
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TimeColumnName string
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ValueColumnName string
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SegmentColumnName string
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}
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func (e *ApplicationInsightsDatasource) executeTimeSeriesQuery(ctx context.Context, originalQueries []*tsdb.Query, timeRange *tsdb.TimeRange) (*tsdb.Response, error) {
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result := &tsdb.Response{
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Results: map[string]*tsdb.QueryResult{},
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}
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queries, err := e.buildQueries(originalQueries, timeRange)
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if err != nil {
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return nil, err
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}
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for _, query := range queries {
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queryRes, err := e.executeQuery(ctx, query)
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if err != nil {
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return nil, err
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}
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result.Results[query.RefID] = queryRes
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}
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return result, nil
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}
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func (e *ApplicationInsightsDatasource) buildQueries(queries []*tsdb.Query, timeRange *tsdb.TimeRange) ([]*ApplicationInsightsQuery, error) {
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applicationInsightsQueries := []*ApplicationInsightsQuery{}
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startTime, err := timeRange.ParseFrom()
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if err != nil {
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return nil, err
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}
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endTime, err := timeRange.ParseTo()
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if err != nil {
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return nil, err
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}
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for _, query := range queries {
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applicationInsightsTarget := query.Model.Get("appInsights").MustMap()
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azlog.Debug("Application Insights", "target", applicationInsightsTarget)
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rawQuery := false
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if asInterface, ok := applicationInsightsTarget["rawQuery"]; ok {
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if asBool, ok := asInterface.(bool); ok {
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rawQuery = asBool
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} else {
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return nil, errors.New("'rawQuery' should be a boolean")
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}
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} else {
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return nil, errors.New("missing 'rawQuery' property")
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}
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if rawQuery {
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var rawQueryString string
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if asInterface, ok := applicationInsightsTarget["rawQueryString"]; ok {
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if asString, ok := asInterface.(string); ok {
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rawQueryString = asString
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}
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}
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if rawQueryString == "" {
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return nil, errors.New("rawQuery requires rawQueryString")
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}
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rawQueryString, err := KqlInterpolate(query, timeRange, fmt.Sprintf("%v", rawQueryString))
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if err != nil {
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return nil, err
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}
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params := url.Values{}
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params.Add("query", rawQueryString)
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applicationInsightsQueries = append(applicationInsightsQueries, &ApplicationInsightsQuery{
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RefID: query.RefId,
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IsRaw: true,
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ApiURL: "query",
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Params: params,
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TimeColumnName: fmt.Sprintf("%v", applicationInsightsTarget["timeColumn"]),
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ValueColumnName: fmt.Sprintf("%v", applicationInsightsTarget["valueColumn"]),
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SegmentColumnName: fmt.Sprintf("%v", applicationInsightsTarget["segmentColumn"]),
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Target: params.Encode(),
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})
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} else {
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alias := ""
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if val, ok := applicationInsightsTarget["alias"]; ok {
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alias = fmt.Sprintf("%v", val)
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}
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azureURL := fmt.Sprintf("metrics/%s", fmt.Sprintf("%v", applicationInsightsTarget["metricName"]))
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timeGrain := fmt.Sprintf("%v", applicationInsightsTarget["timeGrain"])
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timeGrains := applicationInsightsTarget["allowedTimeGrainsMs"]
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if timeGrain == "auto" {
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timeGrain, err = setAutoTimeGrain(query.IntervalMs, timeGrains)
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if err != nil {
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return nil, err
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}
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}
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params := url.Values{}
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params.Add("timespan", fmt.Sprintf("%v/%v", startTime.UTC().Format(time.RFC3339), endTime.UTC().Format(time.RFC3339)))
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if timeGrain != "none" {
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params.Add("interval", timeGrain)
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}
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params.Add("aggregation", fmt.Sprintf("%v", applicationInsightsTarget["aggregation"]))
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dimension := strings.TrimSpace(fmt.Sprintf("%v", applicationInsightsTarget["dimension"]))
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if applicationInsightsTarget["dimension"] != nil && len(dimension) > 0 && !strings.EqualFold(dimension, "none") {
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params.Add("segment", dimension)
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}
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dimensionFilter := strings.TrimSpace(fmt.Sprintf("%v", applicationInsightsTarget["dimensionFilter"]))
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if applicationInsightsTarget["dimensionFilter"] != nil && len(dimensionFilter) > 0 {
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params.Add("filter", fmt.Sprintf("%v", dimensionFilter))
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}
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applicationInsightsQueries = append(applicationInsightsQueries, &ApplicationInsightsQuery{
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RefID: query.RefId,
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IsRaw: false,
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ApiURL: azureURL,
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Params: params,
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Alias: alias,
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Target: params.Encode(),
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})
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}
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}
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return applicationInsightsQueries, nil
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}
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func (e *ApplicationInsightsDatasource) executeQuery(ctx context.Context, query *ApplicationInsightsQuery) (*tsdb.QueryResult, error) {
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queryResult := &tsdb.QueryResult{Meta: simplejson.New(), RefId: query.RefID}
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req, err := e.createRequest(ctx, e.dsInfo)
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if err != nil {
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queryResult.Error = err
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return queryResult, nil
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}
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req.URL.Path = path.Join(req.URL.Path, query.ApiURL)
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req.URL.RawQuery = query.Params.Encode()
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span, ctx := opentracing.StartSpanFromContext(ctx, "application insights query")
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span.SetTag("target", query.Target)
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span.SetTag("datasource_id", e.dsInfo.Id)
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span.SetTag("org_id", e.dsInfo.OrgId)
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defer span.Finish()
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err = opentracing.GlobalTracer().Inject(
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span.Context(),
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opentracing.HTTPHeaders,
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opentracing.HTTPHeadersCarrier(req.Header))
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if err != nil {
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azlog.Warn("failed to inject global tracer")
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}
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azlog.Debug("ApplicationInsights", "Request URL", req.URL.String())
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res, err := ctxhttp.Do(ctx, e.httpClient, req)
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if err != nil {
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queryResult.Error = err
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return queryResult, nil
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}
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body, err := ioutil.ReadAll(res.Body)
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defer res.Body.Close()
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if err != nil {
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return nil, err
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}
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if res.StatusCode/100 != 2 {
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azlog.Error("Request failed", "status", res.Status, "body", string(body))
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return nil, fmt.Errorf(string(body))
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}
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if query.IsRaw {
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queryResult.Series, queryResult.Meta, err = e.parseTimeSeriesFromQuery(body, query)
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if err != nil {
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queryResult.Error = err
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return queryResult, nil
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}
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} else {
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queryResult.Series, err = e.parseTimeSeriesFromMetrics(body, query)
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if err != nil {
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queryResult.Error = err
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return queryResult, nil
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}
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}
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return queryResult, nil
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}
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func (e *ApplicationInsightsDatasource) createRequest(ctx context.Context, dsInfo *models.DataSource) (*http.Request, error) {
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// find plugin
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plugin, ok := plugins.DataSources[dsInfo.Type]
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if !ok {
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return nil, errors.New("Unable to find datasource plugin Azure Application Insights")
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}
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var appInsightsRoute *plugins.AppPluginRoute
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for _, route := range plugin.Routes {
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if route.Path == "appinsights" {
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appInsightsRoute = route
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break
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}
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}
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appInsightsAppId := dsInfo.JsonData.Get("appInsightsAppId").MustString()
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proxyPass := fmt.Sprintf("appinsights/v1/apps/%s", appInsightsAppId)
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u, _ := url.Parse(dsInfo.Url)
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u.Path = path.Join(u.Path, fmt.Sprintf("/v1/apps/%s", appInsightsAppId))
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req, err := http.NewRequest(http.MethodGet, u.String(), nil)
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if err != nil {
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azlog.Error("Failed to create request", "error", err)
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return nil, fmt.Errorf("Failed to create request. error: %v", err)
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}
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req.Header.Set("User-Agent", fmt.Sprintf("Grafana/%s", setting.BuildVersion))
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pluginproxy.ApplyRoute(ctx, req, proxyPass, appInsightsRoute, dsInfo)
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return req, nil
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}
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func (e *ApplicationInsightsDatasource) parseTimeSeriesFromQuery(body []byte, query *ApplicationInsightsQuery) (tsdb.TimeSeriesSlice, *simplejson.Json, error) {
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var data ApplicationInsightsQueryResponse
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err := json.Unmarshal(body, &data)
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if err != nil {
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azlog.Error("Failed to unmarshal Application Insights response", "error", err, "body", string(body))
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return nil, nil, err
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}
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type Metadata struct {
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Columns []string `json:"columns"`
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}
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meta := Metadata{}
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for _, t := range data.Tables {
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if t.Name == "PrimaryResult" {
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timeIndex, valueIndex, segmentIndex := -1, -1, -1
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meta.Columns = make([]string, 0)
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for i, v := range t.Columns {
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meta.Columns = append(meta.Columns, v.Name)
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switch v.Name {
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case query.TimeColumnName:
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timeIndex = i
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case query.ValueColumnName:
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valueIndex = i
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case query.SegmentColumnName:
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segmentIndex = i
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}
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}
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if timeIndex == -1 {
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azlog.Info("no time column specified, returning existing columns, no data")
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return nil, simplejson.NewFromAny(meta), nil
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}
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if valueIndex == -1 {
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azlog.Info("no value column specified, returning existing columns, no data")
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return nil, simplejson.NewFromAny(meta), nil
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}
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var getPoints func([]interface{}) *tsdb.TimeSeriesPoints
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slice := tsdb.TimeSeriesSlice{}
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if segmentIndex == -1 {
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legend := formatApplicationInsightsLegendKey(query.Alias, query.ValueColumnName, "", "")
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series := tsdb.NewTimeSeries(legend, []tsdb.TimePoint{})
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slice = append(slice, series)
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getPoints = func(row []interface{}) *tsdb.TimeSeriesPoints {
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return &series.Points
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}
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} else {
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mapping := map[string]*tsdb.TimeSeriesPoints{}
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getPoints = func(row []interface{}) *tsdb.TimeSeriesPoints {
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segment := fmt.Sprintf("%v", row[segmentIndex])
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if points, ok := mapping[segment]; ok {
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return points
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}
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legend := formatApplicationInsightsLegendKey(query.Alias, query.ValueColumnName, query.SegmentColumnName, segment)
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series := tsdb.NewTimeSeries(legend, []tsdb.TimePoint{})
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slice = append(slice, series)
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mapping[segment] = &series.Points
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return &series.Points
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}
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}
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for _, r := range t.Rows {
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timeStr, ok := r[timeIndex].(string)
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if !ok {
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return nil, simplejson.NewFromAny(meta), errors.New("invalid time value")
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}
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timeValue, err := time.Parse(time.RFC3339Nano, timeStr)
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if err != nil {
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return nil, simplejson.NewFromAny(meta), err
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}
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var value float64
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if value, err = getFloat(r[valueIndex]); err != nil {
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return nil, simplejson.NewFromAny(meta), err
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}
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points := getPoints(r)
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*points = append(*points, tsdb.NewTimePoint(null.FloatFrom(value), float64(timeValue.Unix()*1000)))
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}
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return slice, simplejson.NewFromAny(meta), nil
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}
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}
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return nil, nil, errors.New("could not find table")
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}
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func (e *ApplicationInsightsDatasource) parseTimeSeriesFromMetrics(body []byte, query *ApplicationInsightsQuery) (tsdb.TimeSeriesSlice, error) {
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doc, err := simplejson.NewJson(body)
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if err != nil {
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return nil, err
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}
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value := doc.Get("value").MustMap()
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if value == nil {
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return nil, errors.New("could not find value element")
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}
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endStr, ok := value["end"].(string)
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if !ok {
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return nil, errors.New("missing 'end' value in response")
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}
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endTime, err := time.Parse(time.RFC3339Nano, endStr)
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if err != nil {
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return nil, fmt.Errorf("bad 'end' value: %v", err)
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}
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for k, v := range value {
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switch k {
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case "start":
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case "end":
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case "interval":
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case "segments":
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// we have segments!
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return parseSegmentedValueTimeSeries(query, endTime, v)
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default:
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return parseSingleValueTimeSeries(query, k, endTime, v)
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}
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}
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azlog.Error("Bad response from application insights/metrics", "body", string(body))
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return nil, errors.New("could not find expected values in response")
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}
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func parseSegmentedValueTimeSeries(query *ApplicationInsightsQuery, endTime time.Time, segmentsJson interface{}) (tsdb.TimeSeriesSlice, error) {
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segments, ok := segmentsJson.([]interface{})
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if !ok {
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return nil, errors.New("bad segments value")
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}
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slice := tsdb.TimeSeriesSlice{}
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seriesMap := map[string]*tsdb.TimeSeriesPoints{}
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for _, segment := range segments {
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segmentMap, ok := segment.(map[string]interface{})
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if !ok {
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return nil, errors.New("bad segments value")
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}
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err := processSegment(&slice, segmentMap, query, endTime, seriesMap)
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if err != nil {
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return nil, err
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}
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}
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return slice, nil
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}
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func processSegment(slice *tsdb.TimeSeriesSlice, segment map[string]interface{}, query *ApplicationInsightsQuery, endTime time.Time, pointMap map[string]*tsdb.TimeSeriesPoints) error {
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var segmentName string
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var segmentValue string
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var childSegments []interface{}
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hasChildren := false
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var value float64
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var valueName string
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var ok bool
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var err error
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for k, v := range segment {
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switch k {
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case "start":
|
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case "end":
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endStr, ok := v.(string)
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if !ok {
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return errors.New("missing 'end' value in response")
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||||
}
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endTime, err = time.Parse(time.RFC3339Nano, endStr)
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||||
if err != nil {
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return fmt.Errorf("bad 'end' value: %v", err)
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}
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case "segments":
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childSegments, ok = v.([]interface{})
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if !ok {
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return errors.New("invalid format segments")
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}
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hasChildren = true
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default:
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||||
mapping, hasValues := v.(map[string]interface{})
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if hasValues {
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valueName = k
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value, err = getAggregatedValue(mapping, valueName)
|
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if err != nil {
|
||||
return err
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||||
}
|
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} else {
|
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segmentValue, ok = v.(string)
|
||||
if !ok {
|
||||
return fmt.Errorf("invalid mapping for key %v", k)
|
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}
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segmentName = k
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}
|
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}
|
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}
|
||||
|
||||
if hasChildren {
|
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for _, s := range childSegments {
|
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segmentMap, ok := s.(map[string]interface{})
|
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if !ok {
|
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return errors.New("invalid format segments")
|
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}
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if err := processSegment(slice, segmentMap, query, endTime, pointMap); err != nil {
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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
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||||
*slice = append(*slice, series)
|
||||
pointMap[segmentValue] = points
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||||
}
|
||||
|
||||
*points = append(*points, tsdb.NewTimePoint(null.FloatFrom(value), float64(endTime.Unix()*1000)))
|
||||
}
|
||||
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||||
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)
|
||||
}
|
||||
@@ -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×pan=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×pan=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×pan=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")
|
||||
})
|
||||
})
|
||||
})
|
||||
})
|
||||
})
|
||||
}
|
||||
@@ -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.
|
||||
// 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
|
||||
// formatAzureMonitorLegendKey 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)
|
||||
|
||||
@@ -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"])
|
||||
})
|
||||
})
|
||||
|
||||
@@ -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
|
||||
}
|
||||
@@ -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
|
||||
}
|
||||
|
||||
@@ -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:]
|
||||
}
|
||||
+27
@@ -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
|
||||
]
|
||||
]
|
||||
}
|
||||
]
|
||||
}
|
||||
+43
@@ -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"
|
||||
]
|
||||
]
|
||||
}
|
||||
]
|
||||
}
|
||||
+9
@@ -0,0 +1,9 @@
|
||||
{
|
||||
"value": {
|
||||
"start": "2019-09-13T01:02:03.456789Z",
|
||||
"end": "2019-09-13T02:02:03.456789Z",
|
||||
"value": {
|
||||
"avg": 1.2
|
||||
}
|
||||
}
|
||||
}
|
||||
+23
@@ -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
|
||||
}
|
||||
}
|
||||
]
|
||||
}
|
||||
}
|
||||
+45
@@ -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"
|
||||
}
|
||||
]
|
||||
}
|
||||
]
|
||||
}
|
||||
}
|
||||
@@ -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"`
|
||||
Columns []struct {
|
||||
ColumnName string `json:"ColumnName"`
|
||||
DataType string `json:"DataType"`
|
||||
ColumnType string `json:"ColumnType"`
|
||||
} `json:"Columns"`
|
||||
Rows [][]interface{} `json:"Rows"`
|
||||
} `json:"Tables"`
|
||||
Name string `json:"name"`
|
||||
Columns []struct {
|
||||
Name string `json:"name"`
|
||||
Type string `json:"type"`
|
||||
} `json:"columns"`
|
||||
Rows [][]interface{} `json:"rows"`
|
||||
} `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.
|
||||
|
||||
Reference in New Issue
Block a user