Files
grafana/pkg/services/alerting/executor.go
T

191 lines
4.8 KiB
Go

package alerting
import (
"fmt"
"math"
"github.com/grafana/grafana/pkg/bus"
"github.com/grafana/grafana/pkg/log"
m "github.com/grafana/grafana/pkg/models"
"github.com/grafana/grafana/pkg/services/alerting/alertstates"
"github.com/grafana/grafana/pkg/tsdb"
)
var (
descriptionFmt = "Actual value: %1.2f for %s"
)
type ExecutorImpl struct {
log log.Logger
}
func NewExecutor() *ExecutorImpl {
return &ExecutorImpl{
log: log.New("alerting.executor"),
}
}
type compareFn func(float64, float64) bool
type aggregationFn func(*tsdb.TimeSeries) float64
var operators = map[string]compareFn{
">": func(num1, num2 float64) bool { return num1 > num2 },
">=": func(num1, num2 float64) bool { return num1 >= num2 },
"<": func(num1, num2 float64) bool { return num1 < num2 },
"<=": func(num1, num2 float64) bool { return num1 <= num2 },
"": func(num1, num2 float64) bool { return false },
}
var aggregator = map[string]aggregationFn{
"avg": func(series *tsdb.TimeSeries) float64 {
sum := float64(0)
for _, v := range series.Points {
sum += v[0]
}
return sum / float64(len(series.Points))
},
"sum": func(series *tsdb.TimeSeries) float64 {
sum := float64(0)
for _, v := range series.Points {
sum += v[0]
}
return sum
},
"min": func(series *tsdb.TimeSeries) float64 {
min := series.Points[0][0]
for _, v := range series.Points {
if v[0] < min {
min = v[0]
}
}
return min
},
"max": func(series *tsdb.TimeSeries) float64 {
max := series.Points[0][0]
for _, v := range series.Points {
if v[0] > max {
max = v[0]
}
}
return max
},
"mean": func(series *tsdb.TimeSeries) float64 {
midPosition := int64(math.Floor(float64(len(series.Points)) / float64(2)))
return series.Points[midPosition][0]
},
}
func (e *ExecutorImpl) Execute(job *AlertJob, resultQueue chan *AlertResult) {
timeSeries, err := e.executeQuery(job)
if err != nil {
resultQueue <- &AlertResult{
Error: err,
State: alertstates.Pending,
AlertJob: job,
}
}
result := e.evaluateRule(job.Rule, timeSeries)
result.AlertJob = job
resultQueue <- result
}
func (e *ExecutorImpl) executeQuery(job *AlertJob) (tsdb.TimeSeriesSlice, error) {
getDsInfo := &m.GetDataSourceByIdQuery{
Id: job.Rule.ValueQuery.DatasourceId,
OrgId: job.Rule.OrgId,
}
if err := bus.Dispatch(getDsInfo); err != nil {
return nil, fmt.Errorf("Could not find datasource")
}
req := e.GetRequestForAlertRule(job.Rule, getDsInfo.Result)
result := make(tsdb.TimeSeriesSlice, 0)
resp, err := tsdb.HandleRequest(req)
if err != nil {
return nil, fmt.Errorf("Alerting: GetSeries() tsdb.HandleRequest() error %v", err)
}
for _, v := range resp.Results {
if v.Error != nil {
return nil, fmt.Errorf("Alerting: GetSeries() tsdb.HandleRequest() response error %v", v)
}
result = append(result, v.Series...)
}
return result, nil
}
func (e *ExecutorImpl) GetRequestForAlertRule(rule *AlertRule, datasource *m.DataSource) *tsdb.Request {
log.Debug2("GetRequest", "query", rule.ValueQuery.Query, "from", rule.ValueQuery.From, "datasourceId", datasource.Id)
req := &tsdb.Request{
TimeRange: tsdb.TimeRange{
From: "-" + rule.ValueQuery.From,
To: rule.ValueQuery.To,
},
Queries: []*tsdb.Query{
{
RefId: "A",
Query: rule.ValueQuery.Query,
DataSource: &tsdb.DataSourceInfo{
Id: datasource.Id,
Name: datasource.Name,
PluginId: datasource.Type,
Url: datasource.Url,
},
},
},
}
return req
}
func (e *ExecutorImpl) evaluateRule(rule *AlertRule, series tsdb.TimeSeriesSlice) *AlertResult {
e.log.Debug("Evaluating Alerting Rule", "seriesCount", len(series), "ruleName", rule.Name)
for _, serie := range series {
e.log.Debug("Evaluating series", "series", serie.Name)
if aggregator["avg"] == nil {
continue
}
var aggValue = aggregator["avg"](serie)
var critOperartor = operators[rule.Critical.Operator]
var critResult = critOperartor(aggValue, rule.Critical.Level)
e.log.Debug("Alert execution Crit", "name", serie.Name, "aggValue", aggValue, "operator", rule.Critical.Operator, "level", rule.Critical.Level, "result", critResult)
if critResult {
return &AlertResult{
State: alertstates.Critical,
ActualValue: aggValue,
Description: fmt.Sprintf(descriptionFmt, aggValue, serie.Name),
}
}
var warnOperartor = operators[rule.Warning.Operator]
var warnResult = warnOperartor(aggValue, rule.Warning.Level)
e.log.Debug("Alert execution Warn", "name", serie.Name, "aggValue", aggValue, "operator", rule.Warning.Operator, "level", rule.Warning.Level, "result", warnResult)
if warnResult {
return &AlertResult{
State: alertstates.Warn,
Description: fmt.Sprintf(descriptionFmt, aggValue, serie.Name),
ActualValue: aggValue,
}
}
}
return &AlertResult{State: alertstates.Ok, Description: "Alert is OK!"}
}