Golang log.Warnf函数代码示例

// Send queues the given notification requests for processing.
// Panics if called on a handler that is not running.
func (n *Notifier) Send(alerts ...*model.Alert) {
	n.mtx.Lock()
	defer n.mtx.Unlock()

	// Queue capacity should be significantly larger than a single alert
	// batch could be.
	if d := len(alerts) - n.opts.QueueCapacity; d > 0 {
		alerts = alerts[d:]

		log.Warnf("Alert batch larger than queue capacity, dropping %d alerts", d)
		n.dropped.Add(float64(d))
	}

	// If the queue is full, remove the oldest alerts in favor
	// of newer ones.
	if d := (len(n.queue) + len(alerts)) - n.opts.QueueCapacity; d > 0 {
		n.queue = n.queue[d:]

		log.Warnf("Alert notification queue full, dropping %d alerts", d)
		n.dropped.Add(float64(d))
	}
	n.queue = append(n.queue, alerts...)

	// Notify sending goroutine that there are alerts to be processed.
	n.setMore()
}

// Append implements Storage.
func (s *memorySeriesStorage) Append(sample *model.Sample) {
	for ln, lv := range sample.Metric {
		if len(lv) == 0 {
			delete(sample.Metric, ln)
		}
	}
	if s.getNumChunksToPersist() >= s.maxChunksToPersist {
		log.Warnf(
			"%d chunks waiting for persistence, sample ingestion suspended.",
			s.getNumChunksToPersist(),
		)
		for s.getNumChunksToPersist() >= s.maxChunksToPersist {
			time.Sleep(time.Second)
		}
		log.Warn("Sample ingestion resumed.")
	}
	rawFP := sample.Metric.FastFingerprint()
	s.fpLocker.Lock(rawFP)
	fp, err := s.mapper.mapFP(rawFP, sample.Metric)
	if err != nil {
		log.Errorf("Error while mapping fingerprint %v: %v", rawFP, err)
		s.persistence.setDirty(true)
	}
	if fp != rawFP {
		// Switch locks.
		s.fpLocker.Unlock(rawFP)
		s.fpLocker.Lock(fp)
	}
	series := s.getOrCreateSeries(fp, sample.Metric)

	if sample.Timestamp <= series.lastTime {
		// Don't log and track equal timestamps, as they are a common occurrence
		// when using client-side timestamps (e.g. Pushgateway or federation).
		// It would be even better to also compare the sample values here, but
		// we don't have efficient access to a series's last value.
		if sample.Timestamp != series.lastTime {
			log.Warnf("Ignoring sample with out-of-order timestamp for fingerprint %v (%v): %v is not after %v", fp, series.metric, sample.Timestamp, series.lastTime)
			s.outOfOrderSamplesCount.Inc()
		}
		s.fpLocker.Unlock(fp)
		return
	}
	completedChunksCount := series.add(&model.SamplePair{
		Value:     sample.Value,
		Timestamp: sample.Timestamp,
	})
	s.fpLocker.Unlock(fp)
	s.ingestedSamplesCount.Inc()
	s.incNumChunksToPersist(completedChunksCount)
}

func (t *StorageQueueManager) sendSamples(s model.Samples) {
	t.sendSemaphore <- true

	go func() {
		defer func() {
			<-t.sendSemaphore
		}()

		// Samples are sent to the remote storage on a best-effort basis. If a
		// sample isn't sent correctly the first time, it's simply dropped on the
		// floor.
		begin := time.Now()
		err := t.tsdb.Store(s)
		duration := time.Since(begin).Seconds()

		labelValue := success
		if err != nil {
			log.Warnf("error sending %d samples to remote storage: %s", len(s), err)
			labelValue = failure
			t.failedBatches.Inc()
			t.failedSamples.Add(float64(len(s)))
		}
		t.samplesCount.WithLabelValues(labelValue).Add(float64(len(s)))
		t.sendLatency.Observe(duration)
	}()
}

func lookupAll(name string, qtype uint16) (*dns.Msg, error) {
	conf, err := dns.ClientConfigFromFile(resolvConf)
	if err != nil {
		return nil, fmt.Errorf("could not load resolv.conf: %s", err)
	}

	client := &dns.Client{}
	response := &dns.Msg{}

	for _, server := range conf.Servers {
		servAddr := net.JoinHostPort(server, conf.Port)
		for _, suffix := range conf.Search {
			response, err = lookup(name, qtype, client, servAddr, suffix, false)
			if err != nil {
				log.Warnf("resolving %s.%s failed: %s", name, suffix, err)
				continue
			}
			if len(response.Answer) > 0 {
				return response, nil
			}
		}
		response, err = lookup(name, qtype, client, servAddr, "", false)
		if err == nil {
			return response, nil
		}
	}
	return response, fmt.Errorf("could not resolve %s: No server responded", name)
}

// Run dispatches notifications continuously.
func (n *Notifier) Run() {
	numAMs := len(n.opts.AlertmanagerURLs)
	// Just warn once in the beginning to prevent noisy logs.
	if numAMs == 0 {
		log.Warnf("No AlertManagers configured, not dispatching any alerts")
		return
	}

	for {
		select {
		case <-n.ctx.Done():
			return
		case <-n.more:
		}
		alerts := n.nextBatch()

		if numAMs > 0 {

			if len(alerts) > 0 {
				numErrors := n.sendAll(alerts...)
				// Increment the dropped counter if we could not send
				// successfully to a single AlertManager.
				if numErrors == numAMs {
					n.dropped.Add(float64(len(alerts)))
				}
			}
		} else {
			n.dropped.Add(float64(len(alerts)))
		}
		// If the queue still has items left, kick off the next iteration.
		if n.queueLen() > 0 {
			n.setMore()
		}
	}
}

// Store sends a batch of samples to Graphite.
func (c *Client) Store(samples model.Samples) error {
	conn, err := net.DialTimeout(c.transport, c.address, c.timeout)
	if err != nil {
		return err
	}
	defer conn.Close()

	var buf bytes.Buffer
	for _, s := range samples {
		k := pathFromMetric(s.Metric, c.prefix)
		t := float64(s.Timestamp.UnixNano()) / 1e9
		v := float64(s.Value)
		if math.IsNaN(v) || math.IsInf(v, 0) {
			log.Warnf("cannot send value %f to Graphite,"+
				"skipping sample %#v", v, s)
			continue
		}
		fmt.Fprintf(&buf, "%s %f %f\n", k, v, t)
	}

	_, err = conn.Write(buf.Bytes())
	if err != nil {
		return err
	}

	return nil
}

// Store sends a batch of samples to OpenTSDB via its HTTP API.
func (c *Client) Store(samples model.Samples) error {
	reqs := make([]StoreSamplesRequest, 0, len(samples))
	for _, s := range samples {
		v := float64(s.Value)
		if math.IsNaN(v) || math.IsInf(v, 0) {
			log.Warnf("cannot send value %f to OpenTSDB, skipping sample %#v", v, s)
			continue
		}
		metric := TagValue(s.Metric[model.MetricNameLabel])
		reqs = append(reqs, StoreSamplesRequest{
			Metric:    metric,
			Timestamp: s.Timestamp.Unix(),
			Value:     v,
			Tags:      tagsFromMetric(s.Metric),
		})
	}

	u, err := url.Parse(c.url)
	if err != nil {
		return err
	}

	u.Path = putEndpoint

	buf, err := json.Marshal(reqs)
	if err != nil {
		return err
	}

	resp, err := c.httpClient.Post(
		u.String(),
		contentTypeJSON,
		bytes.NewBuffer(buf),
	)
	if err != nil {
		return err
	}
	defer resp.Body.Close()

	// API returns status code 204 for successful writes.
	// http://opentsdb.net/docs/build/html/api_http/put.html
	if resp.StatusCode == http.StatusNoContent {
		return nil
	}

	// API returns status code 400 on error, encoding error details in the
	// response content in JSON.
	buf, err = ioutil.ReadAll(resp.Body)
	if err != nil {
		return err
	}

	var r map[string]int
	if err := json.Unmarshal(buf, &r); err != nil {
		return err
	}
	return fmt.Errorf("failed to write %d samples to OpenTSDB, %d succeeded", r["failed"], r["success"])
}

func (m *Manager) GetRuleAlertNotifications(rule *AlertingRule, timestamp model.Time) notification.NotificationReqs {
	activeAlerts := rule.ActiveAlerts()
	if len(activeAlerts) == 0 {
		return notification.NotificationReqs{}
	}

	notifications := make(notification.NotificationReqs, 0, len(activeAlerts))
	for _, aa := range activeAlerts {
		if aa.State != StateFiring {
			// BUG: In the future, make AlertManager support pending alerts?
			continue
		}

		// Provide the alert information to the template.
		l := map[string]string{}
		for k, v := range aa.Labels {
			l[string(k)] = string(v)
		}
		tmplData := struct {
			Labels map[string]string
			Value  float64
		}{
			Labels: l,
			Value:  float64(aa.Value),
		}
		// Inject some convenience variables that are easier to remember for users
		// who are not used to Go's templating system.
		defs := "{{$labels := .Labels}}{{$value := .Value}}"

		expand := func(text string) string {
			tmpl := template.NewTemplateExpander(defs+text, "__alert_"+rule.Name(), tmplData, timestamp, m.queryEngine, m.externalURL.Path)
			result, err := tmpl.Expand()
			if err != nil {
				result = err.Error()
				log.Warnf("Error expanding alert template %v with data '%v': %v", rule.Name(), tmplData, err)
			}
			return result
		}

		notifications = append(notifications, &notification.NotificationReq{
			Summary:     expand(rule.summary),
			Description: expand(rule.description),
			Runbook:     rule.runbook,
			Labels: aa.Labels.Merge(model.LabelSet{
				alertNameLabel: model.LabelValue(rule.Name()),
			}),
			Value:        aa.Value,
			ActiveSince:  aa.ActiveSince.Time(),
			RuleString:   rule.String(),
			GeneratorURL: m.externalURL.String() + strutil.GraphLinkForExpression(rule.vector.String()),
		})
	}
	return notifications
}

// Send queues the given notification requests for processing.
// Panics if called on a handler that is not running.
func (n *Notifier) Send(alerts ...*model.Alert) {
	n.mtx.Lock()
	defer n.mtx.Unlock()

	// Attach external labels before relabelling and sending.
	for _, a := range alerts {
		for ln, lv := range n.opts.ExternalLabels {
			if _, ok := a.Labels[ln]; !ok {
				a.Labels[ln] = lv
			}
		}
	}

	alerts = n.relabelAlerts(alerts)

	// Queue capacity should be significantly larger than a single alert
	// batch could be.
	if d := len(alerts) - n.opts.QueueCapacity; d > 0 {
		alerts = alerts[d:]

		log.Warnf("Alert batch larger than queue capacity, dropping %d alerts", d)
		n.dropped.Add(float64(d))
	}

	// If the queue is full, remove the oldest alerts in favor
	// of newer ones.
	if d := (len(n.queue) + len(alerts)) - n.opts.QueueCapacity; d > 0 {
		n.queue = n.queue[d:]

		log.Warnf("Alert notification queue full, dropping %d alerts", d)
		n.dropped.Add(float64(d))
	}
	n.queue = append(n.queue, alerts...)

	// Notify sending goroutine that there are alerts to be processed.
	n.setMore()
}

// eval runs a single evaluation cycle in which all rules are evaluated in parallel.
// In the future a single group will be evaluated sequentially to properly handle
// rule dependency.
func (g *Group) eval() {
	var (
		now = model.Now()
		wg  sync.WaitGroup
	)

	for _, rule := range g.rules {
		wg.Add(1)
		// BUG(julius): Look at fixing thundering herd.
		go func(rule Rule) {
			defer wg.Done()

			start := time.Now()
			evalTotal.Inc()

			vector, err := rule.eval(now, g.opts.QueryEngine)
			if err != nil {
				// Canceled queries are intentional termination of queries. This normally
				// happens on shutdown and thus we skip logging of any errors here.
				if _, ok := err.(promql.ErrQueryCanceled); !ok {
					log.Warnf("Error while evaluating rule %q: %s", rule, err)
				}
				evalFailures.Inc()
			}
			var rtyp ruleType

			switch r := rule.(type) {
			case *AlertingRule:
				rtyp = ruleTypeRecording
				g.sendAlerts(r, now)

			case *RecordingRule:
				rtyp = ruleTypeAlert

			default:
				panic(fmt.Errorf("unknown rule type: %T", rule))
			}

			evalDuration.WithLabelValues(string(rtyp)).Observe(
				float64(time.Since(start)) / float64(time.Second),
			)

			for _, s := range vector {
				g.opts.SampleAppender.Append(s)
			}
		}(rule)
	}
	wg.Wait()
}

// isDegraded returns whether the storage is in "graceful degradation mode",
// which is the case if the number of chunks waiting for persistence has reached
// a percentage of maxChunksToPersist that exceeds
// percentChunksToPersistForDegradation. The method is not goroutine safe (but
// only ever called from the goroutine dealing with series maintenance).
// Changes of degradation mode are logged.
func (s *memorySeriesStorage) isDegraded() bool {
	nowDegraded := s.getNumChunksToPersist() > s.maxChunksToPersist*percentChunksToPersistForDegradation/100
	if s.degraded && !nowDegraded {
		log.Warn("Storage has left graceful degradation mode. Things are back to normal.")
	} else if !s.degraded && nowDegraded {
		log.Warnf(
			"%d chunks waiting for persistence (%d%% of the allowed maximum %d). Storage is now in graceful degradation mode. Series files are not synced anymore if following the adaptive strategy. Checkpoints are not performed more often than every %v. Series maintenance happens as frequently as possible.",
			s.getNumChunksToPersist(),
			s.getNumChunksToPersist()*100/s.maxChunksToPersist,
			s.maxChunksToPersist,
			s.checkpointInterval)
	}
	s.degraded = nowDegraded
	return s.degraded
}

// maybeAddMapping adds a fingerprint mapping to fpm if the FastFingerprint of m is different from fp.
func maybeAddMapping(fp model.Fingerprint, m model.Metric, fpm fpMappings) {
	if rawFP := m.FastFingerprint(); rawFP != fp {
		log.Warnf(
			"Metric %v with fingerprint %v is mapped from raw fingerprint %v.",
			m, fp, rawFP,
		)
		if mappedFPs, ok := fpm[rawFP]; ok {
			mappedFPs[metricToUniqueString(m)] = fp
		} else {
			fpm[rawFP] = map[string]model.Fingerprint{
				metricToUniqueString(m): fp,
			}
		}
	}
}

func (sl *scrapeLoop) append(samples model.Samples) {
	numOutOfOrder := 0

	for _, s := range samples {
		if err := sl.appender.Append(s); err != nil {
			if err == local.ErrOutOfOrderSample {
				numOutOfOrder++
			} else {
				log.Warnf("Error inserting sample: %s", err)
			}
		}
	}
	if numOutOfOrder > 0 {
		log.With("numDropped", numOutOfOrder).Warn("Error on ingesting out-of-order samples")
	}
}

func (t *StorageQueueManager) sendSamples(s model.Samples) {
	// Samples are sent to the remote storage on a best-effort basis. If a
	// sample isn't sent correctly the first time, it's simply dropped on the
	// floor.
	begin := time.Now()
	err := t.tsdb.Store(s)
	duration := time.Since(begin).Seconds()

	labelValue := success
	if err != nil {
		log.Warnf("error sending %d samples to remote storage: %s", len(s), err)
		labelValue = failure
	}
	t.sentSamplesTotal.WithLabelValues(labelValue).Add(float64(len(s)))
	t.sentBatchDuration.WithLabelValues(labelValue).Observe(duration)
}

func (m *Manager) runIteration() {
	now := model.Now()
	wg := sync.WaitGroup{}

	m.Lock()
	rulesSnapshot := make([]Rule, len(m.rules))
	copy(rulesSnapshot, m.rules)
	m.Unlock()

	for _, rule := range rulesSnapshot {
		wg.Add(1)
		// BUG(julius): Look at fixing thundering herd.
		go func(rule Rule) {
			defer wg.Done()

			start := time.Now()
			vector, err := rule.eval(now, m.queryEngine)
			duration := time.Since(start)

			if err != nil {
				evalFailures.Inc()
				log.Warnf("Error while evaluating rule %q: %s", rule, err)
				return
			}

			switch r := rule.(type) {
			case *AlertingRule:
				m.queueAlertNotifications(r, now)
				evalDuration.WithLabelValues(ruleTypeAlerting).Observe(
					float64(duration / time.Millisecond),
				)
			case *RecordingRule:
				evalDuration.WithLabelValues(ruleTypeRecording).Observe(
					float64(duration / time.Millisecond),
				)
			default:
				panic(fmt.Errorf("unknown rule type: %T", rule))
			}

			for _, s := range vector {
				m.sampleAppender.Append(s)
			}
		}(rule)
	}
	wg.Wait()
}