prometheus/rules/group.go
gotjosh 4daaa59c08
Rule Manager: Only query once per alert rule when restoring alert state
Prometheus restores alert state between restarts and updates. For each rule, it looks at the alerts that are meant to be active and then queries the `ALERTS_FOR_STATE` series for _each_ alert within the rules.

If the alert rule has 120 instances (or series) it'll execute the same query with slightly different labels.

This PR changes the approach so that we only query once per alert rule and then match the corresponding alert that we're about to restore against the series-set. While the approach might use a bit more memory at start-up (if even?) the restore proccess is only ran once per restart so I'd consider this a big win.

This builds on top of #13974

Signed-off-by: gotjosh <josue.abreu@gmail.com>
2024-04-24 18:46:05 +01:00

1042 lines
32 KiB
Go

// Copyright 2013 The Prometheus Authors
// Licensed under the Apache License, Version 2.0 (the "License");
// you may not use this file except in compliance with the License.
// You may obtain a copy of the License at
//
// http://www.apache.org/licenses/LICENSE-2.0
//
// Unless required by applicable law or agreed to in writing, software
// distributed under the License is distributed on an "AS IS" BASIS,
// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
// See the License for the specific language governing permissions and
// limitations under the License.
package rules
import (
"context"
"errors"
"math"
"slices"
"strings"
"sync"
"time"
"go.uber.org/atomic"
"github.com/prometheus/prometheus/promql/parser"
"github.com/go-kit/log"
"github.com/go-kit/log/level"
"github.com/prometheus/client_golang/prometheus"
"github.com/prometheus/common/model"
"go.opentelemetry.io/otel"
"go.opentelemetry.io/otel/attribute"
"go.opentelemetry.io/otel/codes"
"github.com/prometheus/prometheus/model/labels"
"github.com/prometheus/prometheus/model/timestamp"
"github.com/prometheus/prometheus/model/value"
"github.com/prometheus/prometheus/promql"
"github.com/prometheus/prometheus/storage"
"github.com/prometheus/prometheus/tsdb/chunkenc"
)
// Group is a set of rules that have a logical relation.
type Group struct {
name string
file string
interval time.Duration
limit int
rules []Rule
seriesInPreviousEval []map[string]labels.Labels // One per Rule.
staleSeries []labels.Labels
opts *ManagerOptions
mtx sync.Mutex
evaluationTime time.Duration
lastEvaluation time.Time // Wall-clock time of most recent evaluation.
lastEvalTimestamp time.Time // Time slot used for most recent evaluation.
shouldRestore bool
markStale bool
done chan struct{}
terminated chan struct{}
managerDone chan struct{}
logger log.Logger
metrics *Metrics
// Rule group evaluation iteration function,
// defaults to DefaultEvalIterationFunc.
evalIterationFunc GroupEvalIterationFunc
// concurrencyController controls the rules evaluation concurrency.
concurrencyController RuleConcurrencyController
}
// GroupEvalIterationFunc is used to implement and extend rule group
// evaluation iteration logic. It is configured in Group.evalIterationFunc,
// and periodically invoked at each group evaluation interval to
// evaluate the rules in the group at that point in time.
// DefaultEvalIterationFunc is the default implementation.
type GroupEvalIterationFunc func(ctx context.Context, g *Group, evalTimestamp time.Time)
type GroupOptions struct {
Name, File string
Interval time.Duration
Limit int
Rules []Rule
ShouldRestore bool
Opts *ManagerOptions
done chan struct{}
EvalIterationFunc GroupEvalIterationFunc
}
// NewGroup makes a new Group with the given name, options, and rules.
func NewGroup(o GroupOptions) *Group {
metrics := o.Opts.Metrics
if metrics == nil {
metrics = NewGroupMetrics(o.Opts.Registerer)
}
key := GroupKey(o.File, o.Name)
metrics.IterationsMissed.WithLabelValues(key)
metrics.IterationsScheduled.WithLabelValues(key)
metrics.EvalTotal.WithLabelValues(key)
metrics.EvalFailures.WithLabelValues(key)
metrics.GroupLastEvalTime.WithLabelValues(key)
metrics.GroupLastDuration.WithLabelValues(key)
metrics.GroupRules.WithLabelValues(key).Set(float64(len(o.Rules)))
metrics.GroupSamples.WithLabelValues(key)
metrics.GroupInterval.WithLabelValues(key).Set(o.Interval.Seconds())
evalIterationFunc := o.EvalIterationFunc
if evalIterationFunc == nil {
evalIterationFunc = DefaultEvalIterationFunc
}
concurrencyController := o.Opts.RuleConcurrencyController
if concurrencyController == nil {
concurrencyController = sequentialRuleEvalController{}
}
return &Group{
name: o.Name,
file: o.File,
interval: o.Interval,
limit: o.Limit,
rules: o.Rules,
shouldRestore: o.ShouldRestore,
opts: o.Opts,
seriesInPreviousEval: make([]map[string]labels.Labels, len(o.Rules)),
done: make(chan struct{}),
managerDone: o.done,
terminated: make(chan struct{}),
logger: log.With(o.Opts.Logger, "file", o.File, "group", o.Name),
metrics: metrics,
evalIterationFunc: evalIterationFunc,
concurrencyController: concurrencyController,
}
}
// Name returns the group name.
func (g *Group) Name() string { return g.name }
// File returns the group's file.
func (g *Group) File() string { return g.file }
// Rules returns the group's rules.
func (g *Group) Rules() []Rule { return g.rules }
// Queryable returns the group's querable.
func (g *Group) Queryable() storage.Queryable { return g.opts.Queryable }
// Context returns the group's context.
func (g *Group) Context() context.Context { return g.opts.Context }
// Interval returns the group's interval.
func (g *Group) Interval() time.Duration { return g.interval }
// Limit returns the group's limit.
func (g *Group) Limit() int { return g.limit }
func (g *Group) Logger() log.Logger { return g.logger }
func (g *Group) run(ctx context.Context) {
defer close(g.terminated)
// Wait an initial amount to have consistently slotted intervals.
evalTimestamp := g.EvalTimestamp(time.Now().UnixNano()).Add(g.interval)
select {
case <-time.After(time.Until(evalTimestamp)):
case <-g.done:
return
}
ctx = promql.NewOriginContext(ctx, map[string]interface{}{
"ruleGroup": map[string]string{
"file": g.File(),
"name": g.Name(),
},
})
// The assumption here is that since the ticker was started after having
// waited for `evalTimestamp` to pass, the ticks will trigger soon
// after each `evalTimestamp + N * g.interval` occurrence.
tick := time.NewTicker(g.interval)
defer tick.Stop()
defer func() {
if !g.markStale {
return
}
go func(now time.Time) {
for _, rule := range g.seriesInPreviousEval {
for _, r := range rule {
g.staleSeries = append(g.staleSeries, r)
}
}
// That can be garbage collected at this point.
g.seriesInPreviousEval = nil
// Wait for 2 intervals to give the opportunity to renamed rules
// to insert new series in the tsdb. At this point if there is a
// renamed rule, it should already be started.
select {
case <-g.managerDone:
case <-time.After(2 * g.interval):
g.cleanupStaleSeries(ctx, now)
}
}(time.Now())
}()
g.evalIterationFunc(ctx, g, evalTimestamp)
if g.shouldRestore {
// If we have to restore, we wait for another Eval to finish.
// The reason behind this is, during first eval (or before it)
// we might not have enough data scraped, and recording rules would not
// have updated the latest values, on which some alerts might depend.
select {
case <-g.done:
return
case <-tick.C:
missed := (time.Since(evalTimestamp) / g.interval) - 1
if missed > 0 {
g.metrics.IterationsMissed.WithLabelValues(GroupKey(g.file, g.name)).Add(float64(missed))
g.metrics.IterationsScheduled.WithLabelValues(GroupKey(g.file, g.name)).Add(float64(missed))
}
evalTimestamp = evalTimestamp.Add((missed + 1) * g.interval)
g.evalIterationFunc(ctx, g, evalTimestamp)
}
restoreStartTime := time.Now()
g.RestoreForState(restoreStartTime)
totalRestoreTimeSeconds := time.Since(restoreStartTime).Seconds()
g.metrics.GroupLastRestoreDuration.WithLabelValues(GroupKey(g.file, g.name)).Set(totalRestoreTimeSeconds)
level.Debug(g.logger).Log("msg", "'for' state restoration completed", "duration_seconds", totalRestoreTimeSeconds)
g.shouldRestore = false
}
for {
select {
case <-g.done:
return
default:
select {
case <-g.done:
return
case <-tick.C:
missed := (time.Since(evalTimestamp) / g.interval) - 1
if missed > 0 {
g.metrics.IterationsMissed.WithLabelValues(GroupKey(g.file, g.name)).Add(float64(missed))
g.metrics.IterationsScheduled.WithLabelValues(GroupKey(g.file, g.name)).Add(float64(missed))
}
evalTimestamp = evalTimestamp.Add((missed + 1) * g.interval)
g.evalIterationFunc(ctx, g, evalTimestamp)
}
}
}
}
func (g *Group) stop() {
close(g.done)
<-g.terminated
}
func (g *Group) hash() uint64 {
l := labels.New(
labels.Label{Name: "name", Value: g.name},
labels.Label{Name: "file", Value: g.file},
)
return l.Hash()
}
// AlertingRules returns the list of the group's alerting rules.
func (g *Group) AlertingRules() []*AlertingRule {
g.mtx.Lock()
defer g.mtx.Unlock()
var alerts []*AlertingRule
for _, rule := range g.rules {
if alertingRule, ok := rule.(*AlertingRule); ok {
alerts = append(alerts, alertingRule)
}
}
slices.SortFunc(alerts, func(a, b *AlertingRule) int {
if a.State() == b.State() {
return strings.Compare(a.Name(), b.Name())
}
return int(b.State() - a.State())
})
return alerts
}
// HasAlertingRules returns true if the group contains at least one AlertingRule.
func (g *Group) HasAlertingRules() bool {
g.mtx.Lock()
defer g.mtx.Unlock()
for _, rule := range g.rules {
if _, ok := rule.(*AlertingRule); ok {
return true
}
}
return false
}
// GetEvaluationTime returns the time in seconds it took to evaluate the rule group.
func (g *Group) GetEvaluationTime() time.Duration {
g.mtx.Lock()
defer g.mtx.Unlock()
return g.evaluationTime
}
// setEvaluationTime sets the time in seconds the last evaluation took.
func (g *Group) setEvaluationTime(dur time.Duration) {
g.metrics.GroupLastDuration.WithLabelValues(GroupKey(g.file, g.name)).Set(dur.Seconds())
g.mtx.Lock()
defer g.mtx.Unlock()
g.evaluationTime = dur
}
// GetLastEvaluation returns the time the last evaluation of the rule group took place.
func (g *Group) GetLastEvaluation() time.Time {
g.mtx.Lock()
defer g.mtx.Unlock()
return g.lastEvaluation
}
// setLastEvaluation updates evaluationTimestamp to the timestamp of when the rule group was last evaluated.
func (g *Group) setLastEvaluation(ts time.Time) {
g.metrics.GroupLastEvalTime.WithLabelValues(GroupKey(g.file, g.name)).Set(float64(ts.UnixNano()) / 1e9)
g.mtx.Lock()
defer g.mtx.Unlock()
g.lastEvaluation = ts
}
// GetLastEvalTimestamp returns the timestamp of the last evaluation.
func (g *Group) GetLastEvalTimestamp() time.Time {
g.mtx.Lock()
defer g.mtx.Unlock()
return g.lastEvalTimestamp
}
// setLastEvalTimestamp updates lastEvalTimestamp to the timestamp of the last evaluation.
func (g *Group) setLastEvalTimestamp(ts time.Time) {
g.mtx.Lock()
defer g.mtx.Unlock()
g.lastEvalTimestamp = ts
}
// EvalTimestamp returns the immediately preceding consistently slotted evaluation time.
func (g *Group) EvalTimestamp(startTime int64) time.Time {
var (
offset = int64(g.hash() % uint64(g.interval))
// This group's evaluation times differ from the perfect time intervals by `offset` nanoseconds.
// But we can only use `% interval` to align with the interval. And `% interval` will always
// align with the perfect time intervals, instead of this group's. Because of this we add
// `offset` _after_ aligning with the perfect time interval.
//
// There can be cases where adding `offset` to the perfect evaluation time can yield a
// timestamp in the future, which is not what EvalTimestamp should do.
// So we subtract one `offset` to make sure that `now - (now % interval) + offset` gives an
// evaluation time in the past.
adjNow = startTime - offset
// Adjust to perfect evaluation intervals.
base = adjNow - (adjNow % int64(g.interval))
// Add one offset to randomize the evaluation times of this group.
next = base + offset
)
return time.Unix(0, next).UTC()
}
func nameAndLabels(rule Rule) string {
return rule.Name() + rule.Labels().String()
}
// CopyState copies the alerting rule and staleness related state from the given group.
//
// Rules are matched based on their name and labels. If there are duplicates, the
// first is matched with the first, second with the second etc.
func (g *Group) CopyState(from *Group) {
g.evaluationTime = from.evaluationTime
g.lastEvaluation = from.lastEvaluation
ruleMap := make(map[string][]int, len(from.rules))
for fi, fromRule := range from.rules {
nameAndLabels := nameAndLabels(fromRule)
l := ruleMap[nameAndLabels]
ruleMap[nameAndLabels] = append(l, fi)
}
for i, rule := range g.rules {
nameAndLabels := nameAndLabels(rule)
indexes := ruleMap[nameAndLabels]
if len(indexes) == 0 {
continue
}
fi := indexes[0]
g.seriesInPreviousEval[i] = from.seriesInPreviousEval[fi]
ruleMap[nameAndLabels] = indexes[1:]
ar, ok := rule.(*AlertingRule)
if !ok {
continue
}
far, ok := from.rules[fi].(*AlertingRule)
if !ok {
continue
}
for fp, a := range far.active {
ar.active[fp] = a
}
}
// Handle deleted and unmatched duplicate rules.
g.staleSeries = from.staleSeries
for fi, fromRule := range from.rules {
nameAndLabels := nameAndLabels(fromRule)
l := ruleMap[nameAndLabels]
if len(l) != 0 {
for _, series := range from.seriesInPreviousEval[fi] {
g.staleSeries = append(g.staleSeries, series)
}
}
}
}
// Eval runs a single evaluation cycle in which all rules are evaluated sequentially.
// Rules can be evaluated concurrently if the `concurrent-rule-eval` feature flag is enabled.
func (g *Group) Eval(ctx context.Context, ts time.Time) {
var (
samplesTotal atomic.Float64
wg sync.WaitGroup
)
for i, rule := range g.rules {
select {
case <-g.done:
return
default:
}
eval := func(i int, rule Rule, cleanup func()) {
if cleanup != nil {
defer cleanup()
}
logger := log.WithPrefix(g.logger, "name", rule.Name(), "index", i)
ctx, sp := otel.Tracer("").Start(ctx, "rule")
sp.SetAttributes(attribute.String("name", rule.Name()))
defer func(t time.Time) {
sp.End()
since := time.Since(t)
g.metrics.EvalDuration.Observe(since.Seconds())
rule.SetEvaluationDuration(since)
rule.SetEvaluationTimestamp(t)
}(time.Now())
if sp.SpanContext().IsSampled() && sp.SpanContext().HasTraceID() {
logger = log.WithPrefix(logger, "trace_id", sp.SpanContext().TraceID())
}
g.metrics.EvalTotal.WithLabelValues(GroupKey(g.File(), g.Name())).Inc()
vector, err := rule.Eval(ctx, ts, g.opts.QueryFunc, g.opts.ExternalURL, g.Limit())
if err != nil {
rule.SetHealth(HealthBad)
rule.SetLastError(err)
sp.SetStatus(codes.Error, err.Error())
g.metrics.EvalFailures.WithLabelValues(GroupKey(g.File(), g.Name())).Inc()
// Canceled queries are intentional termination of queries. This normally
// happens on shutdown and thus we skip logging of any errors here.
var eqc promql.ErrQueryCanceled
if !errors.As(err, &eqc) {
level.Warn(logger).Log("msg", "Evaluating rule failed", "rule", rule, "err", err)
}
return
}
rule.SetHealth(HealthGood)
rule.SetLastError(nil)
samplesTotal.Add(float64(len(vector)))
if ar, ok := rule.(*AlertingRule); ok {
ar.sendAlerts(ctx, ts, g.opts.ResendDelay, g.interval, g.opts.NotifyFunc)
}
var (
numOutOfOrder = 0
numTooOld = 0
numDuplicates = 0
)
app := g.opts.Appendable.Appender(ctx)
seriesReturned := make(map[string]labels.Labels, len(g.seriesInPreviousEval[i]))
defer func() {
if err := app.Commit(); err != nil {
rule.SetHealth(HealthBad)
rule.SetLastError(err)
sp.SetStatus(codes.Error, err.Error())
g.metrics.EvalFailures.WithLabelValues(GroupKey(g.File(), g.Name())).Inc()
level.Warn(logger).Log("msg", "Rule sample appending failed", "err", err)
return
}
g.seriesInPreviousEval[i] = seriesReturned
}()
for _, s := range vector {
if s.H != nil {
_, err = app.AppendHistogram(0, s.Metric, s.T, nil, s.H)
} else {
_, err = app.Append(0, s.Metric, s.T, s.F)
}
if err != nil {
rule.SetHealth(HealthBad)
rule.SetLastError(err)
sp.SetStatus(codes.Error, err.Error())
unwrappedErr := errors.Unwrap(err)
if unwrappedErr == nil {
unwrappedErr = err
}
switch {
case errors.Is(unwrappedErr, storage.ErrOutOfOrderSample):
numOutOfOrder++
level.Debug(logger).Log("msg", "Rule evaluation result discarded", "err", err, "sample", s)
case errors.Is(unwrappedErr, storage.ErrTooOldSample):
numTooOld++
level.Debug(logger).Log("msg", "Rule evaluation result discarded", "err", err, "sample", s)
case errors.Is(unwrappedErr, storage.ErrDuplicateSampleForTimestamp):
numDuplicates++
level.Debug(logger).Log("msg", "Rule evaluation result discarded", "err", err, "sample", s)
default:
level.Warn(logger).Log("msg", "Rule evaluation result discarded", "err", err, "sample", s)
}
} else {
buf := [1024]byte{}
seriesReturned[string(s.Metric.Bytes(buf[:]))] = s.Metric
}
}
if numOutOfOrder > 0 {
level.Warn(logger).Log("msg", "Error on ingesting out-of-order result from rule evaluation", "num_dropped", numOutOfOrder)
}
if numTooOld > 0 {
level.Warn(logger).Log("msg", "Error on ingesting too old result from rule evaluation", "num_dropped", numTooOld)
}
if numDuplicates > 0 {
level.Warn(logger).Log("msg", "Error on ingesting results from rule evaluation with different value but same timestamp", "num_dropped", numDuplicates)
}
for metric, lset := range g.seriesInPreviousEval[i] {
if _, ok := seriesReturned[metric]; !ok {
// Series no longer exposed, mark it stale.
_, err = app.Append(0, lset, timestamp.FromTime(ts), math.Float64frombits(value.StaleNaN))
unwrappedErr := errors.Unwrap(err)
if unwrappedErr == nil {
unwrappedErr = err
}
switch {
case unwrappedErr == nil:
case errors.Is(unwrappedErr, storage.ErrOutOfOrderSample),
errors.Is(unwrappedErr, storage.ErrTooOldSample),
errors.Is(unwrappedErr, storage.ErrDuplicateSampleForTimestamp):
// Do not count these in logging, as this is expected if series
// is exposed from a different rule.
default:
level.Warn(logger).Log("msg", "Adding stale sample failed", "sample", lset.String(), "err", err)
}
}
}
}
// If the rule has no dependencies, it can run concurrently because no other rules in this group depend on its output.
// Try run concurrently if there are slots available.
if ctrl := g.concurrencyController; isRuleEligibleForConcurrentExecution(rule) && ctrl.Allow() {
wg.Add(1)
go eval(i, rule, func() {
wg.Done()
ctrl.Done()
})
} else {
eval(i, rule, nil)
}
}
wg.Wait()
g.metrics.GroupSamples.WithLabelValues(GroupKey(g.File(), g.Name())).Set(samplesTotal.Load())
g.cleanupStaleSeries(ctx, ts)
}
func (g *Group) cleanupStaleSeries(ctx context.Context, ts time.Time) {
if len(g.staleSeries) == 0 {
return
}
app := g.opts.Appendable.Appender(ctx)
for _, s := range g.staleSeries {
// Rule that produced series no longer configured, mark it stale.
_, err := app.Append(0, s, timestamp.FromTime(ts), math.Float64frombits(value.StaleNaN))
unwrappedErr := errors.Unwrap(err)
if unwrappedErr == nil {
unwrappedErr = err
}
switch {
case unwrappedErr == nil:
case errors.Is(unwrappedErr, storage.ErrOutOfOrderSample),
errors.Is(unwrappedErr, storage.ErrTooOldSample),
errors.Is(unwrappedErr, storage.ErrDuplicateSampleForTimestamp):
// Do not count these in logging, as this is expected if series
// is exposed from a different rule.
default:
level.Warn(g.logger).Log("msg", "Adding stale sample for previous configuration failed", "sample", s, "err", err)
}
}
if err := app.Commit(); err != nil {
level.Warn(g.logger).Log("msg", "Stale sample appending for previous configuration failed", "err", err)
} else {
g.staleSeries = nil
}
}
// RestoreForState restores the 'for' state of the alerts
// by looking up last ActiveAt from storage.
func (g *Group) RestoreForState(ts time.Time) {
maxtMS := int64(model.TimeFromUnixNano(ts.UnixNano()))
// We allow restoration only if alerts were active before after certain time.
mint := ts.Add(-g.opts.OutageTolerance)
mintMS := int64(model.TimeFromUnixNano(mint.UnixNano()))
q, err := g.opts.Queryable.Querier(mintMS, maxtMS)
if err != nil {
level.Error(g.logger).Log("msg", "Failed to get Querier", "err", err)
return
}
defer func() {
if err := q.Close(); err != nil {
level.Error(g.logger).Log("msg", "Failed to close Querier", "err", err)
}
}()
for _, rule := range g.Rules() {
alertRule, ok := rule.(*AlertingRule)
if !ok {
continue
}
alertHoldDuration := alertRule.HoldDuration()
if alertHoldDuration < g.opts.ForGracePeriod {
// If alertHoldDuration is already less than grace period, we would not
// like to make it wait for `g.opts.ForGracePeriod` time before firing.
// Hence we skip restoration, which will make it wait for alertHoldDuration.
alertRule.SetRestored(true)
continue
}
sset, err := alertRule.QueryforStateSeries(g.opts.Context, q)
if err != nil {
level.Error(g.logger).Log(
"msg", "Failed to restore 'for' state",
labels.AlertName, alertRule.Name(),
"stage", "Select",
"err", err,
)
continue
}
// No results for this alert rule.
if err == nil {
level.Debug(g.logger).Log("msg", "Failed to find a series to restore the 'for' state", labels.AlertName, alertRule.Name())
continue
}
alertRule.ForEachActiveAlert(func(a *Alert) {
var s storage.Series
// Find the series for the given alert from the set.
for sset.Next() {
if sset.At().Labels().Hash() == a.Labels.Hash() {
s = sset.At()
break
}
}
if s == nil {
return
}
// Series found for the 'for' state.
var t int64
var v float64
it := s.Iterator(nil)
for it.Next() == chunkenc.ValFloat {
t, v = it.At()
}
if it.Err() != nil {
level.Error(g.logger).Log("msg", "Failed to restore 'for' state",
labels.AlertName, alertRule.Name(), "stage", "Iterator", "err", it.Err())
return
}
if value.IsStaleNaN(v) { // Alert was not active.
return
}
downAt := time.Unix(t/1000, 0).UTC()
restoredActiveAt := time.Unix(int64(v), 0).UTC()
timeSpentPending := downAt.Sub(restoredActiveAt)
timeRemainingPending := alertHoldDuration - timeSpentPending
switch {
case timeRemainingPending <= 0:
// It means that alert was firing when prometheus went down.
// In the next Eval, the state of this alert will be set back to
// firing again if it's still firing in that Eval.
// Nothing to be done in this case.
case timeRemainingPending < g.opts.ForGracePeriod:
// (new) restoredActiveAt = (ts + m.opts.ForGracePeriod) - alertHoldDuration
// /* new firing time */ /* moving back by hold duration */
//
// Proof of correctness:
// firingTime = restoredActiveAt.Add(alertHoldDuration)
// = ts + m.opts.ForGracePeriod - alertHoldDuration + alertHoldDuration
// = ts + m.opts.ForGracePeriod
//
// Time remaining to fire = firingTime.Sub(ts)
// = (ts + m.opts.ForGracePeriod) - ts
// = m.opts.ForGracePeriod
restoredActiveAt = ts.Add(g.opts.ForGracePeriod).Add(-alertHoldDuration)
default:
// By shifting ActiveAt to the future (ActiveAt + some_duration),
// the total pending time from the original ActiveAt
// would be `alertHoldDuration + some_duration`.
// Here, some_duration = downDuration.
downDuration := ts.Sub(downAt)
restoredActiveAt = restoredActiveAt.Add(downDuration)
}
a.ActiveAt = restoredActiveAt
level.Debug(g.logger).Log("msg", "'for' state restored",
labels.AlertName, alertRule.Name(), "restored_time", a.ActiveAt.Format(time.RFC850),
"labels", a.Labels.String())
})
alertRule.SetRestored(true)
}
}
// Equals return if two groups are the same.
func (g *Group) Equals(ng *Group) bool {
if g.name != ng.name {
return false
}
if g.file != ng.file {
return false
}
if g.interval != ng.interval {
return false
}
if g.limit != ng.limit {
return false
}
if len(g.rules) != len(ng.rules) {
return false
}
for i, gr := range g.rules {
if gr.String() != ng.rules[i].String() {
return false
}
}
return true
}
// GroupKey group names need not be unique across filenames.
func GroupKey(file, name string) string {
return file + ";" + name
}
// Constants for instrumentation.
const namespace = "prometheus"
// Metrics for rule evaluation.
type Metrics struct {
EvalDuration prometheus.Summary
IterationDuration prometheus.Summary
IterationsMissed *prometheus.CounterVec
IterationsScheduled *prometheus.CounterVec
EvalTotal *prometheus.CounterVec
EvalFailures *prometheus.CounterVec
GroupInterval *prometheus.GaugeVec
GroupLastEvalTime *prometheus.GaugeVec
GroupLastDuration *prometheus.GaugeVec
GroupLastRestoreDuration *prometheus.GaugeVec
GroupRules *prometheus.GaugeVec
GroupSamples *prometheus.GaugeVec
}
// NewGroupMetrics creates a new instance of Metrics and registers it with the provided registerer,
// if not nil.
func NewGroupMetrics(reg prometheus.Registerer) *Metrics {
m := &Metrics{
EvalDuration: prometheus.NewSummary(
prometheus.SummaryOpts{
Namespace: namespace,
Name: "rule_evaluation_duration_seconds",
Help: "The duration for a rule to execute.",
Objectives: map[float64]float64{0.5: 0.05, 0.9: 0.01, 0.99: 0.001},
}),
IterationDuration: prometheus.NewSummary(prometheus.SummaryOpts{
Namespace: namespace,
Name: "rule_group_duration_seconds",
Help: "The duration of rule group evaluations.",
Objectives: map[float64]float64{0.01: 0.001, 0.05: 0.005, 0.5: 0.05, 0.90: 0.01, 0.99: 0.001},
}),
IterationsMissed: prometheus.NewCounterVec(
prometheus.CounterOpts{
Namespace: namespace,
Name: "rule_group_iterations_missed_total",
Help: "The total number of rule group evaluations missed due to slow rule group evaluation.",
},
[]string{"rule_group"},
),
IterationsScheduled: prometheus.NewCounterVec(
prometheus.CounterOpts{
Namespace: namespace,
Name: "rule_group_iterations_total",
Help: "The total number of scheduled rule group evaluations, whether executed or missed.",
},
[]string{"rule_group"},
),
EvalTotal: prometheus.NewCounterVec(
prometheus.CounterOpts{
Namespace: namespace,
Name: "rule_evaluations_total",
Help: "The total number of rule evaluations.",
},
[]string{"rule_group"},
),
EvalFailures: prometheus.NewCounterVec(
prometheus.CounterOpts{
Namespace: namespace,
Name: "rule_evaluation_failures_total",
Help: "The total number of rule evaluation failures.",
},
[]string{"rule_group"},
),
GroupInterval: prometheus.NewGaugeVec(
prometheus.GaugeOpts{
Namespace: namespace,
Name: "rule_group_interval_seconds",
Help: "The interval of a rule group.",
},
[]string{"rule_group"},
),
GroupLastEvalTime: prometheus.NewGaugeVec(
prometheus.GaugeOpts{
Namespace: namespace,
Name: "rule_group_last_evaluation_timestamp_seconds",
Help: "The timestamp of the last rule group evaluation in seconds.",
},
[]string{"rule_group"},
),
GroupLastDuration: prometheus.NewGaugeVec(
prometheus.GaugeOpts{
Namespace: namespace,
Name: "rule_group_last_duration_seconds",
Help: "The duration of the last rule group evaluation.",
},
[]string{"rule_group"},
),
GroupLastRestoreDuration: prometheus.NewGaugeVec(
prometheus.GaugeOpts{
Namespace: namespace,
Name: "rule_group_last_restore_duration_seconds",
Help: "The duration of the last alert rules alerts restoration using the `ALERTS_FOR_STATE` series.",
},
[]string{"rule_group"},
),
GroupRules: prometheus.NewGaugeVec(
prometheus.GaugeOpts{
Namespace: namespace,
Name: "rule_group_rules",
Help: "The number of rules.",
},
[]string{"rule_group"},
),
GroupSamples: prometheus.NewGaugeVec(
prometheus.GaugeOpts{
Namespace: namespace,
Name: "rule_group_last_evaluation_samples",
Help: "The number of samples returned during the last rule group evaluation.",
},
[]string{"rule_group"},
),
}
if reg != nil {
reg.MustRegister(
m.EvalDuration,
m.IterationDuration,
m.IterationsMissed,
m.IterationsScheduled,
m.EvalTotal,
m.EvalFailures,
m.GroupInterval,
m.GroupLastEvalTime,
m.GroupLastDuration,
m.GroupLastRestoreDuration,
m.GroupRules,
m.GroupSamples,
)
}
return m
}
// dependencyMap is a data-structure which contains the relationships between rules within a group.
// It is used to describe the dependency associations between rules in a group whereby one rule uses the
// output metric produced by another rule in its expression (i.e. as its "input").
type dependencyMap map[Rule][]Rule
// dependents returns the count of rules which use the output of the given rule as one of their inputs.
func (m dependencyMap) dependents(r Rule) int {
return len(m[r])
}
// dependencies returns the count of rules on which the given rule is dependent for input.
func (m dependencyMap) dependencies(r Rule) int {
if len(m) == 0 {
return 0
}
var count int
for _, children := range m {
for _, child := range children {
if child == r {
count++
}
}
}
return count
}
// isIndependent determines whether the given rule is not dependent on another rule for its input, nor is any other rule
// dependent on its output.
func (m dependencyMap) isIndependent(r Rule) bool {
if m == nil {
return false
}
return m.dependents(r)+m.dependencies(r) == 0
}
// buildDependencyMap builds a data-structure which contains the relationships between rules within a group.
//
// Alert rules, by definition, cannot have any dependents - but they can have dependencies. Any recording rule on whose
// output an Alert rule depends will not be able to run concurrently.
//
// There is a class of rule expressions which are considered "indeterminate", because either relationships cannot be
// inferred, or concurrent evaluation of rules depending on these series would produce undefined/unexpected behaviour:
// - wildcard queriers like {cluster="prod1"} which would match every series with that label selector
// - any "meta" series (series produced by Prometheus itself) like ALERTS, ALERTS_FOR_STATE
//
// Rules which are independent can run concurrently with no side-effects.
func buildDependencyMap(rules []Rule) dependencyMap {
dependencies := make(dependencyMap)
if len(rules) <= 1 {
// No relationships if group has 1 or fewer rules.
return dependencies
}
inputs := make(map[string][]Rule, len(rules))
outputs := make(map[string][]Rule, len(rules))
var indeterminate bool
for _, rule := range rules {
if indeterminate {
break
}
name := rule.Name()
outputs[name] = append(outputs[name], rule)
parser.Inspect(rule.Query(), func(node parser.Node, path []parser.Node) error {
if n, ok := node.(*parser.VectorSelector); ok {
// A wildcard metric expression means we cannot reliably determine if this rule depends on any other,
// which means we cannot safely run any rules concurrently.
if n.Name == "" && len(n.LabelMatchers) > 0 {
indeterminate = true
return nil
}
// Rules which depend on "meta-metrics" like ALERTS and ALERTS_FOR_STATE will have undefined behaviour
// if they run concurrently.
if n.Name == alertMetricName || n.Name == alertForStateMetricName {
indeterminate = true
return nil
}
inputs[n.Name] = append(inputs[n.Name], rule)
}
return nil
})
}
if indeterminate {
return nil
}
for output, outRules := range outputs {
for _, outRule := range outRules {
if inRules, found := inputs[output]; found && len(inRules) > 0 {
dependencies[outRule] = append(dependencies[outRule], inRules...)
}
}
}
return dependencies
}
func isRuleEligibleForConcurrentExecution(rule Rule) bool {
return rule.NoDependentRules() && rule.NoDependencyRules()
}