mirror of
https://github.com/prometheus/prometheus.git
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479 lines
13 KiB
Go
479 lines
13 KiB
Go
// Copyright 2013 The Prometheus Authors
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// Licensed under the Apache License, Version 2.0 (the "License");
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// you may not use this file except in compliance with the License.
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// You may obtain a copy of the License at
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//
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// http://www.apache.org/licenses/LICENSE-2.0
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//
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// Unless required by applicable law or agreed to in writing, software
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// distributed under the License is distributed on an "AS IS" BASIS,
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// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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// See the License for the specific language governing permissions and
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// limitations under the License.
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package remote
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import (
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"math"
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"sync"
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"time"
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"golang.org/x/time/rate"
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"github.com/prometheus/client_golang/prometheus"
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"github.com/prometheus/common/log"
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"github.com/prometheus/common/model"
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"github.com/prometheus/prometheus/config"
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"github.com/prometheus/prometheus/relabel"
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)
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// String constants for instrumentation.
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const (
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namespace = "prometheus"
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subsystem = "remote_storage"
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queue = "queue"
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// We track samples in/out and how long pushes take using an Exponentially
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// Weighted Moving Average.
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ewmaWeight = 0.2
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shardUpdateDuration = 10 * time.Second
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// Allow 30% too many shards before scaling down.
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shardToleranceFraction = 0.3
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// Limit to 1 log event every 10s
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logRateLimit = 0.1
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logBurst = 10
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)
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var (
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succeededSamplesTotal = prometheus.NewCounterVec(
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prometheus.CounterOpts{
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Namespace: namespace,
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Subsystem: subsystem,
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Name: "succeeded_samples_total",
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Help: "Total number of samples successfully sent to remote storage.",
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},
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[]string{queue},
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)
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failedSamplesTotal = prometheus.NewCounterVec(
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prometheus.CounterOpts{
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Namespace: namespace,
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Subsystem: subsystem,
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Name: "failed_samples_total",
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Help: "Total number of samples which failed on send to remote storage.",
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},
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[]string{queue},
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)
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droppedSamplesTotal = prometheus.NewCounterVec(
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prometheus.CounterOpts{
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Namespace: namespace,
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Subsystem: subsystem,
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Name: "dropped_samples_total",
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Help: "Total number of samples which were dropped due to the queue being full.",
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},
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[]string{queue},
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)
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sentBatchDuration = prometheus.NewHistogramVec(
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prometheus.HistogramOpts{
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Namespace: namespace,
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Subsystem: subsystem,
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Name: "sent_batch_duration_seconds",
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Help: "Duration of sample batch send calls to the remote storage.",
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Buckets: prometheus.DefBuckets,
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},
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[]string{queue},
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)
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queueLength = prometheus.NewGaugeVec(
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prometheus.GaugeOpts{
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Namespace: namespace,
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Subsystem: subsystem,
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Name: "queue_length",
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Help: "The number of processed samples queued to be sent to the remote storage.",
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},
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[]string{queue},
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)
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queueCapacity = prometheus.NewGaugeVec(
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prometheus.GaugeOpts{
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Namespace: namespace,
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Subsystem: subsystem,
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Name: "queue_capacity",
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Help: "The capacity of the queue of samples to be sent to the remote storage.",
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},
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[]string{queue},
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)
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numShards = prometheus.NewGaugeVec(
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prometheus.GaugeOpts{
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Namespace: namespace,
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Subsystem: subsystem,
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Name: "shards",
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Help: "The number of shards used for parallel sending to the remote storage.",
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},
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[]string{queue},
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)
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)
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func init() {
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prometheus.MustRegister(succeededSamplesTotal)
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prometheus.MustRegister(failedSamplesTotal)
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prometheus.MustRegister(droppedSamplesTotal)
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prometheus.MustRegister(sentBatchDuration)
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prometheus.MustRegister(queueLength)
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prometheus.MustRegister(queueCapacity)
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prometheus.MustRegister(numShards)
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}
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// StorageClient defines an interface for sending a batch of samples to an
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// external timeseries database.
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type StorageClient interface {
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// Store stores the given samples in the remote storage.
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Store(model.Samples) error
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// Name identifies the remote storage implementation.
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Name() string
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}
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// QueueManager manages a queue of samples to be sent to the Storage
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// indicated by the provided StorageClient.
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type QueueManager struct {
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cfg config.QueueConfig
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externalLabels model.LabelSet
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relabelConfigs []*config.RelabelConfig
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client StorageClient
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queueName string
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logLimiter *rate.Limiter
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shardsMtx sync.Mutex
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shards *shards
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numShards int
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reshardChan chan int
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quit chan struct{}
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wg sync.WaitGroup
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samplesIn, samplesOut, samplesOutDuration *ewmaRate
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integralAccumulator float64
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}
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// NewQueueManager builds a new QueueManager.
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func NewQueueManager(cfg config.QueueConfig, externalLabels model.LabelSet, relabelConfigs []*config.RelabelConfig, client StorageClient) *QueueManager {
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t := &QueueManager{
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cfg: cfg,
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externalLabels: externalLabels,
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relabelConfigs: relabelConfigs,
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client: client,
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queueName: client.Name(),
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logLimiter: rate.NewLimiter(logRateLimit, logBurst),
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numShards: 1,
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reshardChan: make(chan int),
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quit: make(chan struct{}),
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samplesIn: newEWMARate(ewmaWeight, shardUpdateDuration),
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samplesOut: newEWMARate(ewmaWeight, shardUpdateDuration),
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samplesOutDuration: newEWMARate(ewmaWeight, shardUpdateDuration),
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}
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t.shards = t.newShards(t.numShards)
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numShards.WithLabelValues(t.queueName).Set(float64(t.numShards))
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queueCapacity.WithLabelValues(t.queueName).Set(float64(t.cfg.Capacity))
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return t
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}
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// Append queues a sample to be sent to the remote storage. It drops the
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// sample on the floor if the queue is full.
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// Always returns nil.
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func (t *QueueManager) Append(s *model.Sample) error {
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var snew model.Sample
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snew = *s
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snew.Metric = s.Metric.Clone()
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for ln, lv := range t.externalLabels {
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if _, ok := s.Metric[ln]; !ok {
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snew.Metric[ln] = lv
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}
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}
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snew.Metric = model.Metric(
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relabel.Process(model.LabelSet(snew.Metric), t.relabelConfigs...))
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if snew.Metric == nil {
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return nil
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}
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t.shardsMtx.Lock()
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enqueued := t.shards.enqueue(&snew)
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t.shardsMtx.Unlock()
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if enqueued {
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queueLength.WithLabelValues(t.queueName).Inc()
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} else {
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droppedSamplesTotal.WithLabelValues(t.queueName).Inc()
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if t.logLimiter.Allow() {
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log.Warn("Remote storage queue full, discarding sample. Multiple subsequent messages of this kind may be suppressed.")
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}
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}
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return nil
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}
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// NeedsThrottling implements storage.SampleAppender. It will always return
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// false as a remote storage drops samples on the floor if backlogging instead
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// of asking for throttling.
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func (*QueueManager) NeedsThrottling() bool {
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return false
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}
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// Start the queue manager sending samples to the remote storage.
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// Does not block.
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func (t *QueueManager) Start() {
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t.wg.Add(2)
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go t.updateShardsLoop()
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go t.reshardLoop()
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t.shardsMtx.Lock()
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defer t.shardsMtx.Unlock()
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t.shards.start()
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}
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// Stop stops sending samples to the remote storage and waits for pending
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// sends to complete.
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func (t *QueueManager) Stop() {
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log.Infof("Stopping remote storage...")
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close(t.quit)
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t.wg.Wait()
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t.shardsMtx.Lock()
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defer t.shardsMtx.Unlock()
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t.shards.stop()
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log.Info("Remote storage stopped.")
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}
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func (t *QueueManager) updateShardsLoop() {
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defer t.wg.Done()
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ticker := time.Tick(shardUpdateDuration)
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for {
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select {
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case <-ticker:
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t.calculateDesiredShards()
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case <-t.quit:
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return
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}
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}
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}
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func (t *QueueManager) calculateDesiredShards() {
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t.samplesIn.tick()
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t.samplesOut.tick()
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t.samplesOutDuration.tick()
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// We use the number of incoming samples as a prediction of how much work we
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// will need to do next iteration. We add to this any pending samples
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// (received - sent) so we can catch up with any backlog. We use the average
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// outgoing batch latency to work out how many shards we need.
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var (
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samplesIn = t.samplesIn.rate()
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samplesOut = t.samplesOut.rate()
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samplesPending = samplesIn - samplesOut
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samplesOutDuration = t.samplesOutDuration.rate()
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)
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// We use an integral accumulator, like in a PID, to help dampen oscillation.
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t.integralAccumulator = t.integralAccumulator + (samplesPending * 0.1)
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if samplesOut <= 0 {
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return
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}
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var (
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timePerSample = samplesOutDuration / samplesOut
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desiredShards = (timePerSample * (samplesIn + samplesPending + t.integralAccumulator)) / float64(time.Second)
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)
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log.Debugf("QueueManager.calculateDesiredShards samplesIn=%f, samplesOut=%f, samplesPending=%f, desiredShards=%f",
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samplesIn, samplesOut, samplesPending, desiredShards)
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// Changes in the number of shards must be greater than shardToleranceFraction.
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var (
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lowerBound = float64(t.numShards) * (1. - shardToleranceFraction)
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upperBound = float64(t.numShards) * (1. + shardToleranceFraction)
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)
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log.Debugf("QueueManager.updateShardsLoop %f <= %f <= %f", lowerBound, desiredShards, upperBound)
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if lowerBound <= desiredShards && desiredShards <= upperBound {
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return
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}
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numShards := int(math.Ceil(desiredShards))
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if numShards > t.cfg.MaxShards {
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numShards = t.cfg.MaxShards
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} else if numShards < 1 {
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numShards = 1
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}
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if numShards == t.numShards {
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return
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}
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// Resharding can take some time, and we want this loop
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// to stay close to shardUpdateDuration.
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select {
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case t.reshardChan <- numShards:
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log.Infof("Remote storage resharding from %d to %d shards.", t.numShards, numShards)
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t.numShards = numShards
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default:
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log.Infof("Currently resharding, skipping.")
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}
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}
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func (t *QueueManager) reshardLoop() {
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defer t.wg.Done()
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for {
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select {
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case numShards := <-t.reshardChan:
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t.reshard(numShards)
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case <-t.quit:
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return
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}
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}
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}
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func (t *QueueManager) reshard(n int) {
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numShards.WithLabelValues(t.queueName).Set(float64(n))
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t.shardsMtx.Lock()
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newShards := t.newShards(n)
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oldShards := t.shards
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t.shards = newShards
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t.shardsMtx.Unlock()
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oldShards.stop()
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// We start the newShards after we have stopped (the therefore completely
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// flushed) the oldShards, to guarantee we only every deliver samples in
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// order.
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newShards.start()
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}
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type shards struct {
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qm *QueueManager
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queues []chan *model.Sample
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done chan struct{}
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wg sync.WaitGroup
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}
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func (t *QueueManager) newShards(numShards int) *shards {
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queues := make([]chan *model.Sample, numShards)
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for i := 0; i < numShards; i++ {
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queues[i] = make(chan *model.Sample, t.cfg.Capacity)
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}
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s := &shards{
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qm: t,
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queues: queues,
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done: make(chan struct{}),
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}
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s.wg.Add(numShards)
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return s
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}
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func (s *shards) len() int {
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return len(s.queues)
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}
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func (s *shards) start() {
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for i := 0; i < len(s.queues); i++ {
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go s.runShard(i)
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}
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}
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func (s *shards) stop() {
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for _, shard := range s.queues {
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close(shard)
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}
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s.wg.Wait()
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}
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func (s *shards) enqueue(sample *model.Sample) bool {
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s.qm.samplesIn.incr(1)
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fp := sample.Metric.FastFingerprint()
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shard := uint64(fp) % uint64(len(s.queues))
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select {
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case s.queues[shard] <- sample:
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return true
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default:
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return false
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}
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}
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func (s *shards) runShard(i int) {
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defer s.wg.Done()
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queue := s.queues[i]
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// Send batches of at most MaxSamplesPerSend samples to the remote storage.
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// If we have fewer samples than that, flush them out after a deadline
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// anyways.
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pendingSamples := model.Samples{}
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for {
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select {
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case sample, ok := <-queue:
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if !ok {
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if len(pendingSamples) > 0 {
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log.Debugf("Flushing %d samples to remote storage...", len(pendingSamples))
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s.sendSamples(pendingSamples)
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log.Debugf("Done flushing.")
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}
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return
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}
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queueLength.WithLabelValues(s.qm.queueName).Dec()
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pendingSamples = append(pendingSamples, sample)
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for len(pendingSamples) >= s.qm.cfg.MaxSamplesPerSend {
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s.sendSamples(pendingSamples[:s.qm.cfg.MaxSamplesPerSend])
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pendingSamples = pendingSamples[s.qm.cfg.MaxSamplesPerSend:]
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}
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case <-time.After(s.qm.cfg.BatchSendDeadline):
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if len(pendingSamples) > 0 {
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s.sendSamples(pendingSamples)
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pendingSamples = pendingSamples[:0]
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}
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}
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}
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}
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func (s *shards) sendSamples(samples model.Samples) {
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begin := time.Now()
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s.sendSamplesWithBackoff(samples)
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// These counters are used to calculate the dynamic sharding, and as such
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// should be maintained irrespective of success or failure.
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s.qm.samplesOut.incr(int64(len(samples)))
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s.qm.samplesOutDuration.incr(int64(time.Since(begin)))
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}
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// sendSamples to the remote storage with backoff for recoverable errors.
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func (s *shards) sendSamplesWithBackoff(samples model.Samples) {
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backoff := s.qm.cfg.MinBackoff
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for retries := s.qm.cfg.MaxRetries; retries > 0; retries-- {
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begin := time.Now()
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err := s.qm.client.Store(samples)
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sentBatchDuration.WithLabelValues(s.qm.queueName).Observe(time.Since(begin).Seconds())
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if err == nil {
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succeededSamplesTotal.WithLabelValues(s.qm.queueName).Add(float64(len(samples)))
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return
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}
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log.Warnf("Error sending %d samples to remote storage: %s", len(samples), err)
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if _, ok := err.(recoverableError); !ok {
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break
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}
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time.Sleep(backoff)
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backoff = backoff * 2
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if backoff > s.qm.cfg.MaxBackoff {
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backoff = s.qm.cfg.MaxBackoff
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}
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}
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failedSamplesTotal.WithLabelValues(s.qm.queueName).Add(float64(len(samples)))
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}
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