Files
grafana/pkg/services/ngalert/schedule/jitter.go
Yuri Tseretyan fa1e6cce5e Alerting: Rule backtesting with experimental UI (#115525)
* add function to convert StateTransition to LokiEntry
* add QueryResultBuilder
* update backtesting to produce result similar to historian
* make shouldRecord public
* filter out noop transitions
* add experimental front-end
* add new fields
* move conversion of api model to AlertRule to validation
* add extra labels
* calculate tick timestamp using the same logic as in scheduler
* implement correct logic of calculating first evaluation timestamp
* add uid, group and folder uid they are needed for jitter strategy

* add JitterOffsetInDuration and JitterStrategy.String()

* add config `backtesting_max_evaluations` to [unified_alerting] (not documented for now)

* remove obsolete tests

* elevate permisisons for backtesting endpoint
* move backtesting to separate dir
2025-12-26 16:55:57 -05:00

82 lines
2.7 KiB
Go

package schedule
import (
"fmt"
"time"
"github.com/grafana/grafana-plugin-sdk-go/data"
"github.com/grafana/grafana/pkg/services/featuremgmt"
ngmodels "github.com/grafana/grafana/pkg/services/ngalert/models"
"github.com/grafana/grafana/pkg/setting"
)
// JitterStrategy represents a modifier to alert rule timing that affects how evaluations are distributed.
type JitterStrategy int
func (s JitterStrategy) String() string {
return [...]string{"never", "by group", "by rule"}[s]
}
const (
JitterNever JitterStrategy = iota
JitterByGroup
JitterByRule
)
// JitterStrategyFrom returns the JitterStrategy indicated by the current Grafana feature toggles.
func JitterStrategyFrom(cfg setting.UnifiedAlertingSettings, toggles featuremgmt.FeatureToggles) JitterStrategy {
strategy := JitterByGroup
if cfg.DisableJitter {
return JitterNever
}
if toggles == nil {
return strategy
}
//nolint:staticcheck // not yet migrated to OpenFeature
if toggles.IsEnabledGlobally(featuremgmt.FlagJitterAlertRulesWithinGroups) {
strategy = JitterByRule
}
return strategy
}
// jitterOffsetInTicks gives the jitter offset for a rule, in terms of a number of ticks relative to its interval and a base interval.
// The resulting number of ticks is non-negative. We assume the rule is well-formed and has an IntervalSeconds greater to or equal than baseInterval.
func jitterOffsetInTicks(r *ngmodels.AlertRule, baseInterval time.Duration, strategy JitterStrategy) int64 {
if strategy == JitterNever {
return 0
}
itemFrequency := r.IntervalSeconds / int64(baseInterval.Seconds())
offset := jitterHash(r, strategy) % uint64(itemFrequency)
// Offset is always nonnegative and less than int64.max, because above we mod by itemFrequency which fits in the positive half of int64.
// offset <= itemFrequency <= int64.max
// So, this will not overflow and produce a negative offset.
res := int64(offset)
// Regardless, take an absolute value anyway for an extra layer of safety in case the above logic ever changes.
// Our contract requires that the result is nonnegative and less than int64.max.
if res < 0 {
return -res
}
return res
}
// JitterOffsetInDuration gives the jitter offset for a rule, in terms of a duration relative to its interval and a base interval.
func JitterOffsetInDuration(r *ngmodels.AlertRule, baseInterval time.Duration, strategy JitterStrategy) time.Duration {
return time.Duration(jitterOffsetInTicks(r, baseInterval, strategy)) * baseInterval
}
func jitterHash(r *ngmodels.AlertRule, strategy JitterStrategy) uint64 {
ls := data.Labels{
"name": r.RuleGroup,
"file": r.NamespaceUID,
"orgId": fmt.Sprint(r.OrgID),
}
if strategy == JitterByRule {
ls["uid"] = r.UID
}
return uint64(ls.Fingerprint())
}