// 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 remote import ( "math" "sync" "time" "golang.org/x/time/rate" "github.com/prometheus/client_golang/prometheus" "github.com/prometheus/common/log" "github.com/prometheus/common/model" "github.com/prometheus/prometheus/config" "github.com/prometheus/prometheus/relabel" ) // String constants for instrumentation. const ( namespace = "prometheus" subsystem = "remote_storage" queue = "queue" // We track samples in/out and how long pushes take using an Exponentially // Weighted Moving Average. ewmaWeight = 0.2 shardUpdateDuration = 10 * time.Second // Allow 30% too many shards before scaling down. shardToleranceFraction = 0.3 // Limit to 1 log event every 10s logRateLimit = 0.1 logBurst = 10 ) var ( succeededSamplesTotal = prometheus.NewCounterVec( prometheus.CounterOpts{ Namespace: namespace, Subsystem: subsystem, Name: "succeeded_samples_total", Help: "Total number of samples successfully sent to remote storage.", }, []string{queue}, ) failedSamplesTotal = prometheus.NewCounterVec( prometheus.CounterOpts{ Namespace: namespace, Subsystem: subsystem, Name: "failed_samples_total", Help: "Total number of samples which failed on send to remote storage.", }, []string{queue}, ) droppedSamplesTotal = prometheus.NewCounterVec( prometheus.CounterOpts{ Namespace: namespace, Subsystem: subsystem, Name: "dropped_samples_total", Help: "Total number of samples which were dropped due to the queue being full.", }, []string{queue}, ) sentBatchDuration = prometheus.NewHistogramVec( prometheus.HistogramOpts{ Namespace: namespace, Subsystem: subsystem, Name: "sent_batch_duration_seconds", Help: "Duration of sample batch send calls to the remote storage.", Buckets: prometheus.DefBuckets, }, []string{queue}, ) queueLength = prometheus.NewGaugeVec( prometheus.GaugeOpts{ Namespace: namespace, Subsystem: subsystem, Name: "queue_length", Help: "The number of processed samples queued to be sent to the remote storage.", }, []string{queue}, ) queueCapacity = prometheus.NewGaugeVec( prometheus.GaugeOpts{ Namespace: namespace, Subsystem: subsystem, Name: "queue_capacity", Help: "The capacity of the queue of samples to be sent to the remote storage.", }, []string{queue}, ) numShards = prometheus.NewGaugeVec( prometheus.GaugeOpts{ Namespace: namespace, Subsystem: subsystem, Name: "shards", Help: "The number of shards used for parallel sending to the remote storage.", }, []string{queue}, ) ) func init() { prometheus.MustRegister(succeededSamplesTotal) prometheus.MustRegister(failedSamplesTotal) prometheus.MustRegister(droppedSamplesTotal) prometheus.MustRegister(sentBatchDuration) prometheus.MustRegister(queueLength) prometheus.MustRegister(queueCapacity) prometheus.MustRegister(numShards) } // StorageClient defines an interface for sending a batch of samples to an // external timeseries database. type StorageClient interface { // Store stores the given samples in the remote storage. Store(model.Samples) error // Name identifies the remote storage implementation. Name() string } // QueueManager manages a queue of samples to be sent to the Storage // indicated by the provided StorageClient. type QueueManager struct { cfg config.QueueManagerConfig externalLabels model.LabelSet relabelConfigs []*config.RelabelConfig client StorageClient queueName string logLimiter *rate.Limiter shardsMtx sync.Mutex shards *shards numShards int reshardChan chan int quit chan struct{} wg sync.WaitGroup samplesIn, samplesOut, samplesOutDuration *ewmaRate integralAccumulator float64 } // NewQueueManager builds a new QueueManager. func NewQueueManager(cfg config.QueueManagerConfig, externalLabels model.LabelSet, relabelConfigs []*config.RelabelConfig, client StorageClient) *QueueManager { t := &QueueManager{ cfg: cfg, externalLabels: externalLabels, relabelConfigs: relabelConfigs, client: client, queueName: client.Name(), logLimiter: rate.NewLimiter(logRateLimit, logBurst), numShards: 1, reshardChan: make(chan int), quit: make(chan struct{}), samplesIn: newEWMARate(ewmaWeight, shardUpdateDuration), samplesOut: newEWMARate(ewmaWeight, shardUpdateDuration), samplesOutDuration: newEWMARate(ewmaWeight, shardUpdateDuration), } t.shards = t.newShards(t.numShards) numShards.WithLabelValues(t.queueName).Set(float64(t.numShards)) queueCapacity.WithLabelValues(t.queueName).Set(float64(t.cfg.QueueCapacity)) return t } // Append queues a sample to be sent to the remote storage. It drops the // sample on the floor if the queue is full. // Always returns nil. func (t *QueueManager) Append(s *model.Sample) error { var snew model.Sample snew = *s snew.Metric = s.Metric.Clone() for ln, lv := range t.externalLabels { if _, ok := s.Metric[ln]; !ok { snew.Metric[ln] = lv } } snew.Metric = model.Metric( relabel.Process(model.LabelSet(snew.Metric), t.relabelConfigs...)) if snew.Metric == nil { return nil } t.shardsMtx.Lock() enqueued := t.shards.enqueue(&snew) t.shardsMtx.Unlock() if enqueued { queueLength.WithLabelValues(t.queueName).Inc() } else { droppedSamplesTotal.WithLabelValues(t.queueName).Inc() if t.logLimiter.Allow() { log.Warn("Remote storage queue full, discarding sample. Multiple subsequent messages of this kind may be suppressed.") } } return nil } // NeedsThrottling implements storage.SampleAppender. It will always return // false as a remote storage drops samples on the floor if backlogging instead // of asking for throttling. func (*QueueManager) NeedsThrottling() bool { return false } // Start the queue manager sending samples to the remote storage. // Does not block. func (t *QueueManager) Start() { t.wg.Add(2) go t.updateShardsLoop() go t.reshardLoop() t.shardsMtx.Lock() defer t.shardsMtx.Unlock() t.shards.start() } // Stop stops sending samples to the remote storage and waits for pending // sends to complete. func (t *QueueManager) Stop() { log.Infof("Stopping remote storage...") close(t.quit) t.wg.Wait() t.shardsMtx.Lock() defer t.shardsMtx.Unlock() t.shards.stop() log.Info("Remote storage stopped.") } func (t *QueueManager) updateShardsLoop() { defer t.wg.Done() ticker := time.Tick(shardUpdateDuration) for { select { case <-ticker: t.calculateDesiredShards() case <-t.quit: return } } } func (t *QueueManager) calculateDesiredShards() { t.samplesIn.tick() t.samplesOut.tick() t.samplesOutDuration.tick() // We use the number of incoming samples as a prediction of how much work we // will need to do next iteration. We add to this any pending samples // (received - sent) so we can catch up with any backlog. We use the average // outgoing batch latency to work out how many shards we need. var ( samplesIn = t.samplesIn.rate() samplesOut = t.samplesOut.rate() samplesPending = samplesIn - samplesOut samplesOutDuration = t.samplesOutDuration.rate() ) // We use an integral accumulator, like in a PID, to help dampen oscillation. t.integralAccumulator = t.integralAccumulator + (samplesPending * 0.1) if samplesOut <= 0 { return } var ( timePerSample = samplesOutDuration / samplesOut desiredShards = (timePerSample * (samplesIn + samplesPending + t.integralAccumulator)) / float64(time.Second) ) log.Debugf("QueueManager.calculateDesiredShards samplesIn=%f, samplesOut=%f, samplesPending=%f, desiredShards=%f", samplesIn, samplesOut, samplesPending, desiredShards) // Changes in the number of shards must be greater than shardToleranceFraction. var ( lowerBound = float64(t.numShards) * (1. - shardToleranceFraction) upperBound = float64(t.numShards) * (1. + shardToleranceFraction) ) log.Debugf("QueueManager.updateShardsLoop %f <= %f <= %f", lowerBound, desiredShards, upperBound) if lowerBound <= desiredShards && desiredShards <= upperBound { return } numShards := int(math.Ceil(desiredShards)) if numShards > t.cfg.MaxShards { numShards = t.cfg.MaxShards } if numShards == t.numShards { return } // Resharding can take some time, and we want this loop // to stay close to shardUpdateDuration. select { case t.reshardChan <- numShards: log.Infof("Remote storage resharding from %d to %d shards.", t.numShards, numShards) t.numShards = numShards default: log.Infof("Currently resharding, skipping.") } } func (t *QueueManager) reshardLoop() { defer t.wg.Done() for { select { case numShards := <-t.reshardChan: t.reshard(numShards) case <-t.quit: return } } } func (t *QueueManager) reshard(n int) { numShards.WithLabelValues(t.queueName).Set(float64(n)) t.shardsMtx.Lock() newShards := t.newShards(n) oldShards := t.shards t.shards = newShards t.shardsMtx.Unlock() oldShards.stop() // We start the newShards after we have stopped (the therefore completely // flushed) the oldShards, to guarantee we only every deliver samples in // order. newShards.start() } type shards struct { qm *QueueManager queues []chan *model.Sample done chan struct{} wg sync.WaitGroup } func (t *QueueManager) newShards(numShards int) *shards { queues := make([]chan *model.Sample, numShards) for i := 0; i < numShards; i++ { queues[i] = make(chan *model.Sample, t.cfg.QueueCapacity) } s := &shards{ qm: t, queues: queues, done: make(chan struct{}), } s.wg.Add(numShards) return s } func (s *shards) len() int { return len(s.queues) } func (s *shards) start() { for i := 0; i < len(s.queues); i++ { go s.runShard(i) } } func (s *shards) stop() { for _, shard := range s.queues { close(shard) } s.wg.Wait() } func (s *shards) enqueue(sample *model.Sample) bool { s.qm.samplesIn.incr(1) fp := sample.Metric.FastFingerprint() shard := uint64(fp) % uint64(len(s.queues)) select { case s.queues[shard] <- sample: return true default: return false } } func (s *shards) runShard(i int) { defer s.wg.Done() queue := s.queues[i] // Send batches of at most MaxSamplesPerSend samples to the remote storage. // If we have fewer samples than that, flush them out after a deadline // anyways. pendingSamples := model.Samples{} for { select { case sample, ok := <-queue: if !ok { if len(pendingSamples) > 0 { log.Debugf("Flushing %d samples to remote storage...", len(pendingSamples)) s.sendSamples(pendingSamples) log.Debugf("Done flushing.") } return } queueLength.WithLabelValues(s.qm.queueName).Dec() pendingSamples = append(pendingSamples, sample) for len(pendingSamples) >= s.qm.cfg.MaxSamplesPerSend { s.sendSamples(pendingSamples[:s.qm.cfg.MaxSamplesPerSend]) pendingSamples = pendingSamples[s.qm.cfg.MaxSamplesPerSend:] } case <-time.After(s.qm.cfg.BatchSendDeadline): if len(pendingSamples) > 0 { s.sendSamples(pendingSamples) pendingSamples = pendingSamples[:0] } } } } func (s *shards) sendSamples(samples model.Samples) { begin := time.Now() s.sendSamplesWithBackoff(samples) // These counters are used to calculate the dynamic sharding, and as such // should be maintained irrespective of success or failure. s.qm.samplesOut.incr(int64(len(samples))) s.qm.samplesOutDuration.incr(int64(time.Since(begin))) } // sendSamples to the remote storage with backoff for recoverable errors. func (s *shards) sendSamplesWithBackoff(samples model.Samples) { backoff := s.qm.cfg.MinBackoff for retries := s.qm.cfg.MaxRetries; retries > 0; retries-- { begin := time.Now() err := s.qm.client.Store(samples) sentBatchDuration.WithLabelValues(s.qm.queueName).Observe(time.Since(begin).Seconds()) if err == nil { succeededSamplesTotal.WithLabelValues(s.qm.queueName).Add(float64(len(samples))) return } log.Warnf("Error sending %d samples to remote storage: %s", len(samples), err) if _, ok := err.(recoverableError); !ok { break } time.Sleep(backoff) backoff = backoff * 2 if backoff > s.qm.cfg.MaxBackoff { backoff = s.qm.cfg.MaxBackoff } } failedSamplesTotal.WithLabelValues(s.qm.queueName).Add(float64(len(samples))) }