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prometheus/main.go

399 lines
12 KiB

// Copyright 2013 Prometheus Team
// 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 main
import (
"flag"
"os"
"os/signal"
"syscall"
"time"
"github.com/golang/glog"
"github.com/prometheus/client_golang/extraction"
clientmodel "github.com/prometheus/client_golang/model"
"github.com/prometheus/prometheus/config"
"github.com/prometheus/prometheus/notification"
"github.com/prometheus/prometheus/retrieval"
"github.com/prometheus/prometheus/rules"
"github.com/prometheus/prometheus/storage/metric"
Add optional sample replication to OpenTSDB. Prometheus needs long-term storage. Since we don't have enough resources to build our own timeseries storage from scratch ontop of Riak, Cassandra or a similar distributed datastore at the moment, we're planning on using OpenTSDB as long-term storage for Prometheus. It's data model is roughly compatible with that of Prometheus, with some caveats. As a first step, this adds write-only replication from Prometheus to OpenTSDB, with the following things worth noting: 1) I tried to keep the integration lightweight, meaning that anything related to OpenTSDB is isolated to its own package and only main knows about it (essentially it tees all samples to both the existing storage and TSDB). It's not touching the existing TieredStorage at all to avoid more complexity in that area. This might change in the future, especially if we decide to implement a read path for OpenTSDB through Prometheus as well. 2) Backpressure while sending to OpenTSDB is handled by simply dropping samples on the floor when the in-memory queue of samples destined for OpenTSDB runs full. Prometheus also only attempts to send samples once, rather than implementing a complex retry algorithm. Thus, replication to OpenTSDB is best-effort for now. If needed, this may be extended in the future. 3) Samples are sent in batches of limited size to OpenTSDB. The optimal batch size, timeout parameters, etc. may need to be adjusted in the future. 4) OpenTSDB has different rules for legal characters in tag (label) values. While Prometheus allows any characters in label values, OpenTSDB limits them to a to z, A to Z, 0 to 9, -, _, . and /. Currently any illegal characters in Prometheus label values are simply replaced by an underscore. Especially when integrating OpenTSDB with the read path in Prometheus, we'll need to reconsider this: either we'll need to introduce the same limitations for Prometheus labels or escape/encode illegal characters in OpenTSDB in such a way that they are fully decodable again when reading through Prometheus, so that corresponding timeseries in both systems match in their labelsets. Change-Id: I8394c9c55dbac3946a0fa497f566d5e6e2d600b5
11 years ago
"github.com/prometheus/prometheus/storage/remote"
"github.com/prometheus/prometheus/storage/remote/opentsdb"
"github.com/prometheus/prometheus/web"
"github.com/prometheus/prometheus/web/api"
)
const deletionBatchSize = 100
// Commandline flags.
var (
configFile = flag.String("configFile", "prometheus.conf", "Prometheus configuration file name.")
metricsStoragePath = flag.String("metricsStoragePath", "/tmp/metrics", "Base path for metrics storage.")
alertmanagerUrl = flag.String("alertmanager.url", "", "The URL of the alert manager to send notifications to.")
Add optional sample replication to OpenTSDB. Prometheus needs long-term storage. Since we don't have enough resources to build our own timeseries storage from scratch ontop of Riak, Cassandra or a similar distributed datastore at the moment, we're planning on using OpenTSDB as long-term storage for Prometheus. It's data model is roughly compatible with that of Prometheus, with some caveats. As a first step, this adds write-only replication from Prometheus to OpenTSDB, with the following things worth noting: 1) I tried to keep the integration lightweight, meaning that anything related to OpenTSDB is isolated to its own package and only main knows about it (essentially it tees all samples to both the existing storage and TSDB). It's not touching the existing TieredStorage at all to avoid more complexity in that area. This might change in the future, especially if we decide to implement a read path for OpenTSDB through Prometheus as well. 2) Backpressure while sending to OpenTSDB is handled by simply dropping samples on the floor when the in-memory queue of samples destined for OpenTSDB runs full. Prometheus also only attempts to send samples once, rather than implementing a complex retry algorithm. Thus, replication to OpenTSDB is best-effort for now. If needed, this may be extended in the future. 3) Samples are sent in batches of limited size to OpenTSDB. The optimal batch size, timeout parameters, etc. may need to be adjusted in the future. 4) OpenTSDB has different rules for legal characters in tag (label) values. While Prometheus allows any characters in label values, OpenTSDB limits them to a to z, A to Z, 0 to 9, -, _, . and /. Currently any illegal characters in Prometheus label values are simply replaced by an underscore. Especially when integrating OpenTSDB with the read path in Prometheus, we'll need to reconsider this: either we'll need to introduce the same limitations for Prometheus labels or escape/encode illegal characters in OpenTSDB in such a way that they are fully decodable again when reading through Prometheus, so that corresponding timeseries in both systems match in their labelsets. Change-Id: I8394c9c55dbac3946a0fa497f566d5e6e2d600b5
11 years ago
remoteTSDBUrl = flag.String("storage.remote.url", "", "The URL of the OpenTSDB instance to send samples to.")
remoteTSDBTimeout = flag.Duration("storage.remote.timeout", 30*time.Second, "The timeout to use when sending samples to OpenTSDB.")
samplesQueueCapacity = flag.Int("storage.queue.samplesCapacity", 4096, "The size of the unwritten samples queue.")
diskAppendQueueCapacity = flag.Int("storage.queue.diskAppendCapacity", 1000000, "The size of the queue for items that are pending writing to disk.")
memoryAppendQueueCapacity = flag.Int("storage.queue.memoryAppendCapacity", 10000, "The size of the queue for items that are pending writing to memory.")
headCompactInterval = flag.Duration("compact.headInterval", 3*time.Hour, "The amount of time between head compactions.")
bodyCompactInterval = flag.Duration("compact.bodyInterval", 5*time.Hour, "The amount of time between body compactions.")
tailCompactInterval = flag.Duration("compact.tailInterval", 7*time.Hour, "The amount of time between tail compactions.")
headGroupSize = flag.Int("compact.headGroupSize", 500, "The minimum group size for head samples.")
bodyGroupSize = flag.Int("compact.bodyGroupSize", 5000, "The minimum group size for body samples.")
tailGroupSize = flag.Int("compact.tailGroupSize", 10000, "The minimum group size for tail samples.")
headAge = flag.Duration("compact.headAgeInclusiveness", 5*time.Minute, "The relative inclusiveness of head samples.")
bodyAge = flag.Duration("compact.bodyAgeInclusiveness", time.Hour, "The relative inclusiveness of body samples.")
tailAge = flag.Duration("compact.tailAgeInclusiveness", 24*time.Hour, "The relative inclusiveness of tail samples.")
deleteInterval = flag.Duration("delete.interval", 11*time.Hour, "The amount of time between deletion of old values.")
deleteAge = flag.Duration("delete.ageMaximum", 15*24*time.Hour, "The relative maximum age for values before they are deleted.")
arenaFlushInterval = flag.Duration("arena.flushInterval", 15*time.Minute, "The period at which the in-memory arena is flushed to disk.")
arenaTTL = flag.Duration("arena.ttl", 10*time.Minute, "The relative age of values to purge to disk from memory.")
notificationQueueCapacity = flag.Int("alertmanager.notificationQueueCapacity", 100, "The size of the queue for pending alert manager notifications.")
concurrentRetrievalAllowance = flag.Int("concurrentRetrievalAllowance", 15, "The number of concurrent metrics retrieval requests allowed.")
printVersion = flag.Bool("version", false, "print version information")
)
type prometheus struct {
headCompactionTimer *time.Ticker
bodyCompactionTimer *time.Ticker
tailCompactionTimer *time.Ticker
deletionTimer *time.Ticker
curationSema chan bool
stopBackgroundOperations chan bool
unwrittenSamples chan *extraction.Result
Add optional sample replication to OpenTSDB. Prometheus needs long-term storage. Since we don't have enough resources to build our own timeseries storage from scratch ontop of Riak, Cassandra or a similar distributed datastore at the moment, we're planning on using OpenTSDB as long-term storage for Prometheus. It's data model is roughly compatible with that of Prometheus, with some caveats. As a first step, this adds write-only replication from Prometheus to OpenTSDB, with the following things worth noting: 1) I tried to keep the integration lightweight, meaning that anything related to OpenTSDB is isolated to its own package and only main knows about it (essentially it tees all samples to both the existing storage and TSDB). It's not touching the existing TieredStorage at all to avoid more complexity in that area. This might change in the future, especially if we decide to implement a read path for OpenTSDB through Prometheus as well. 2) Backpressure while sending to OpenTSDB is handled by simply dropping samples on the floor when the in-memory queue of samples destined for OpenTSDB runs full. Prometheus also only attempts to send samples once, rather than implementing a complex retry algorithm. Thus, replication to OpenTSDB is best-effort for now. If needed, this may be extended in the future. 3) Samples are sent in batches of limited size to OpenTSDB. The optimal batch size, timeout parameters, etc. may need to be adjusted in the future. 4) OpenTSDB has different rules for legal characters in tag (label) values. While Prometheus allows any characters in label values, OpenTSDB limits them to a to z, A to Z, 0 to 9, -, _, . and /. Currently any illegal characters in Prometheus label values are simply replaced by an underscore. Especially when integrating OpenTSDB with the read path in Prometheus, we'll need to reconsider this: either we'll need to introduce the same limitations for Prometheus labels or escape/encode illegal characters in OpenTSDB in such a way that they are fully decodable again when reading through Prometheus, so that corresponding timeseries in both systems match in their labelsets. Change-Id: I8394c9c55dbac3946a0fa497f566d5e6e2d600b5
11 years ago
ruleManager rules.RuleManager
targetManager retrieval.TargetManager
notifications chan notification.NotificationReqs
storage *metric.TieredStorage
remoteTSDBQueue *remote.TSDBQueueManager
curationState metric.CurationStateUpdater
}
func (p *prometheus) interruptHandler() {
notifier := make(chan os.Signal)
signal.Notify(notifier, os.Interrupt, syscall.SIGTERM)
<-notifier
glog.Warning("Received SIGINT/SIGTERM; Exiting gracefully...")
p.close()
os.Exit(0)
}
func (p *prometheus) compact(olderThan time.Duration, groupSize int) error {
select {
case p.curationSema <- true:
default:
glog.Warningf("Deferred compaction for %s and %s due to existing operation.", olderThan, groupSize)
return nil
}
defer func() {
<-p.curationSema
}()
processor := metric.NewCompactionProcessor(&metric.CompactionProcessorOptions{
MaximumMutationPoolBatch: groupSize * 3,
MinimumGroupSize: groupSize,
})
defer processor.Close()
curator := metric.NewCurator(&metric.CuratorOptions{
Stop: p.stopBackgroundOperations,
ViewQueue: p.storage.ViewQueue,
})
defer curator.Close()
Use custom timestamp type for sample timestamps and related code. So far we've been using Go's native time.Time for anything related to sample timestamps. Since the range of time.Time is much bigger than what we need, this has created two problems: - there could be time.Time values which were out of the range/precision of the time type that we persist to disk, therefore causing incorrectly ordered keys. One bug caused by this was: https://github.com/prometheus/prometheus/issues/367 It would be good to use a timestamp type that's more closely aligned with what the underlying storage supports. - sizeof(time.Time) is 192, while Prometheus should be ok with a single 64-bit Unix timestamp (possibly even a 32-bit one). Since we store samples in large numbers, this seriously affects memory usage. Furthermore, copying/working with the data will be faster if it's smaller. *MEMORY USAGE RESULTS* Initial memory usage comparisons for a running Prometheus with 1 timeseries and 100,000 samples show roughly a 13% decrease in total (VIRT) memory usage. In my tests, this advantage for some reason decreased a bit the more samples the timeseries had (to 5-7% for millions of samples). This I can't fully explain, but perhaps garbage collection issues were involved. *WHEN TO USE THE NEW TIMESTAMP TYPE* The new clientmodel.Timestamp type should be used whenever time calculations are either directly or indirectly related to sample timestamps. For example: - the timestamp of a sample itself - all kinds of watermarks - anything that may become or is compared to a sample timestamp (like the timestamp passed into Target.Scrape()). When to still use time.Time: - for measuring durations/times not related to sample timestamps, like duration telemetry exporting, timers that indicate how frequently to execute some action, etc. *NOTE ON OPERATOR OPTIMIZATION TESTS* We don't use operator optimization code anymore, but it still lives in the code as dead code. It still has tests, but I couldn't get all of them to pass with the new timestamp format. I commented out the failing cases for now, but we should probably remove the dead code soon. I just didn't want to do that in the same change as this. Change-Id: I821787414b0debe85c9fffaeb57abd453727af0f
11 years ago
return curator.Run(olderThan, clientmodel.Now(), processor, p.storage.DiskStorage.CurationRemarks, p.storage.DiskStorage.MetricSamples, p.storage.DiskStorage.MetricHighWatermarks, p.curationState)
}
func (p *prometheus) delete(olderThan time.Duration, batchSize int) error {
select {
case p.curationSema <- true:
default:
glog.Warningf("Deferred deletion for %s due to existing operation.", olderThan)
return nil
}
processor := metric.NewDeletionProcessor(&metric.DeletionProcessorOptions{
MaximumMutationPoolBatch: batchSize,
})
defer processor.Close()
curator := metric.NewCurator(&metric.CuratorOptions{
Stop: p.stopBackgroundOperations,
ViewQueue: p.storage.ViewQueue,
})
defer curator.Close()
Use custom timestamp type for sample timestamps and related code. So far we've been using Go's native time.Time for anything related to sample timestamps. Since the range of time.Time is much bigger than what we need, this has created two problems: - there could be time.Time values which were out of the range/precision of the time type that we persist to disk, therefore causing incorrectly ordered keys. One bug caused by this was: https://github.com/prometheus/prometheus/issues/367 It would be good to use a timestamp type that's more closely aligned with what the underlying storage supports. - sizeof(time.Time) is 192, while Prometheus should be ok with a single 64-bit Unix timestamp (possibly even a 32-bit one). Since we store samples in large numbers, this seriously affects memory usage. Furthermore, copying/working with the data will be faster if it's smaller. *MEMORY USAGE RESULTS* Initial memory usage comparisons for a running Prometheus with 1 timeseries and 100,000 samples show roughly a 13% decrease in total (VIRT) memory usage. In my tests, this advantage for some reason decreased a bit the more samples the timeseries had (to 5-7% for millions of samples). This I can't fully explain, but perhaps garbage collection issues were involved. *WHEN TO USE THE NEW TIMESTAMP TYPE* The new clientmodel.Timestamp type should be used whenever time calculations are either directly or indirectly related to sample timestamps. For example: - the timestamp of a sample itself - all kinds of watermarks - anything that may become or is compared to a sample timestamp (like the timestamp passed into Target.Scrape()). When to still use time.Time: - for measuring durations/times not related to sample timestamps, like duration telemetry exporting, timers that indicate how frequently to execute some action, etc. *NOTE ON OPERATOR OPTIMIZATION TESTS* We don't use operator optimization code anymore, but it still lives in the code as dead code. It still has tests, but I couldn't get all of them to pass with the new timestamp format. I commented out the failing cases for now, but we should probably remove the dead code soon. I just didn't want to do that in the same change as this. Change-Id: I821787414b0debe85c9fffaeb57abd453727af0f
11 years ago
return curator.Run(olderThan, clientmodel.Now(), processor, p.storage.DiskStorage.CurationRemarks, p.storage.DiskStorage.MetricSamples, p.storage.DiskStorage.MetricHighWatermarks, p.curationState)
}
func (p *prometheus) close() {
select {
case p.curationSema <- true:
default:
}
if p.headCompactionTimer != nil {
p.headCompactionTimer.Stop()
}
if p.bodyCompactionTimer != nil {
p.bodyCompactionTimer.Stop()
}
if p.tailCompactionTimer != nil {
p.tailCompactionTimer.Stop()
}
if p.deletionTimer != nil {
p.deletionTimer.Stop()
}
// Stop any currently active curation (deletion or compaction).
if len(p.stopBackgroundOperations) == 0 {
p.stopBackgroundOperations <- true
}
p.ruleManager.Stop()
p.targetManager.Stop()
close(p.unwrittenSamples)
p.storage.Close()
Add optional sample replication to OpenTSDB. Prometheus needs long-term storage. Since we don't have enough resources to build our own timeseries storage from scratch ontop of Riak, Cassandra or a similar distributed datastore at the moment, we're planning on using OpenTSDB as long-term storage for Prometheus. It's data model is roughly compatible with that of Prometheus, with some caveats. As a first step, this adds write-only replication from Prometheus to OpenTSDB, with the following things worth noting: 1) I tried to keep the integration lightweight, meaning that anything related to OpenTSDB is isolated to its own package and only main knows about it (essentially it tees all samples to both the existing storage and TSDB). It's not touching the existing TieredStorage at all to avoid more complexity in that area. This might change in the future, especially if we decide to implement a read path for OpenTSDB through Prometheus as well. 2) Backpressure while sending to OpenTSDB is handled by simply dropping samples on the floor when the in-memory queue of samples destined for OpenTSDB runs full. Prometheus also only attempts to send samples once, rather than implementing a complex retry algorithm. Thus, replication to OpenTSDB is best-effort for now. If needed, this may be extended in the future. 3) Samples are sent in batches of limited size to OpenTSDB. The optimal batch size, timeout parameters, etc. may need to be adjusted in the future. 4) OpenTSDB has different rules for legal characters in tag (label) values. While Prometheus allows any characters in label values, OpenTSDB limits them to a to z, A to Z, 0 to 9, -, _, . and /. Currently any illegal characters in Prometheus label values are simply replaced by an underscore. Especially when integrating OpenTSDB with the read path in Prometheus, we'll need to reconsider this: either we'll need to introduce the same limitations for Prometheus labels or escape/encode illegal characters in OpenTSDB in such a way that they are fully decodable again when reading through Prometheus, so that corresponding timeseries in both systems match in their labelsets. Change-Id: I8394c9c55dbac3946a0fa497f566d5e6e2d600b5
11 years ago
if p.remoteTSDBQueue != nil {
p.remoteTSDBQueue.Close()
}
close(p.notifications)
close(p.stopBackgroundOperations)
}
func main() {
// TODO(all): Future additions to main should be, where applicable, glumped
// into the prometheus struct above---at least where the scoping of the entire
// server is concerned.
flag.Parse()
versionInfoTmpl.Execute(os.Stdout, BuildInfo)
if *printVersion {
os.Exit(0)
}
conf, err := config.LoadFromFile(*configFile)
if err != nil {
glog.Fatalf("Error loading configuration from %s: %v", *configFile, err)
}
ts, err := metric.NewTieredStorage(uint(*diskAppendQueueCapacity), 100, *arenaFlushInterval, *arenaTTL, *metricsStoragePath)
if err != nil {
glog.Fatal("Error opening storage: ", err)
}
Add optional sample replication to OpenTSDB. Prometheus needs long-term storage. Since we don't have enough resources to build our own timeseries storage from scratch ontop of Riak, Cassandra or a similar distributed datastore at the moment, we're planning on using OpenTSDB as long-term storage for Prometheus. It's data model is roughly compatible with that of Prometheus, with some caveats. As a first step, this adds write-only replication from Prometheus to OpenTSDB, with the following things worth noting: 1) I tried to keep the integration lightweight, meaning that anything related to OpenTSDB is isolated to its own package and only main knows about it (essentially it tees all samples to both the existing storage and TSDB). It's not touching the existing TieredStorage at all to avoid more complexity in that area. This might change in the future, especially if we decide to implement a read path for OpenTSDB through Prometheus as well. 2) Backpressure while sending to OpenTSDB is handled by simply dropping samples on the floor when the in-memory queue of samples destined for OpenTSDB runs full. Prometheus also only attempts to send samples once, rather than implementing a complex retry algorithm. Thus, replication to OpenTSDB is best-effort for now. If needed, this may be extended in the future. 3) Samples are sent in batches of limited size to OpenTSDB. The optimal batch size, timeout parameters, etc. may need to be adjusted in the future. 4) OpenTSDB has different rules for legal characters in tag (label) values. While Prometheus allows any characters in label values, OpenTSDB limits them to a to z, A to Z, 0 to 9, -, _, . and /. Currently any illegal characters in Prometheus label values are simply replaced by an underscore. Especially when integrating OpenTSDB with the read path in Prometheus, we'll need to reconsider this: either we'll need to introduce the same limitations for Prometheus labels or escape/encode illegal characters in OpenTSDB in such a way that they are fully decodable again when reading through Prometheus, so that corresponding timeseries in both systems match in their labelsets. Change-Id: I8394c9c55dbac3946a0fa497f566d5e6e2d600b5
11 years ago
var remoteTSDBQueue *remote.TSDBQueueManager = nil
if *remoteTSDBUrl == "" {
glog.Warningf("No TSDB URL provided; not sending any samples to long-term storage")
} else {
openTSDB := opentsdb.NewClient(*remoteTSDBUrl, *remoteTSDBTimeout)
remoteTSDBQueue = remote.NewTSDBQueueManager(openTSDB, 512)
go remoteTSDBQueue.Run()
}
unwrittenSamples := make(chan *extraction.Result, *samplesQueueCapacity)
ingester := &retrieval.MergeLabelsIngester{
Labels: conf.GlobalLabels(),
CollisionPrefix: clientmodel.ExporterLabelPrefix,
Ingester: retrieval.ChannelIngester(unwrittenSamples),
}
// Coprime numbers, fool!
headCompactionTimer := time.NewTicker(*headCompactInterval)
bodyCompactionTimer := time.NewTicker(*bodyCompactInterval)
tailCompactionTimer := time.NewTicker(*tailCompactInterval)
deletionTimer := time.NewTicker(*deleteInterval)
// Queue depth will need to be exposed
targetManager := retrieval.NewTargetManager(ingester, *concurrentRetrievalAllowance)
targetManager.AddTargetsFromConfig(conf)
notifications := make(chan notification.NotificationReqs, *notificationQueueCapacity)
// Queue depth will need to be exposed
ruleManager := rules.NewRuleManager(&rules.RuleManagerOptions{
Results: unwrittenSamples,
Notifications: notifications,
EvaluationInterval: conf.EvaluationInterval(),
Storage: ts,
PrometheusUrl: web.MustBuildServerUrl(),
})
if err := ruleManager.AddRulesFromConfig(conf); err != nil {
glog.Fatal("Error loading rule files: ", err)
}
go ruleManager.Run()
notificationHandler := notification.NewNotificationHandler(*alertmanagerUrl, notifications)
go notificationHandler.Run()
flags := map[string]string{}
flag.VisitAll(func(f *flag.Flag) {
flags[f.Name] = f.Value.String()
})
prometheusStatus := &web.PrometheusStatusHandler{
BuildInfo: BuildInfo,
Config: conf.String(),
RuleManager: ruleManager,
TargetPools: targetManager.Pools(),
Flags: flags,
Birth: time.Now(),
}
alertsHandler := &web.AlertsHandler{
RuleManager: ruleManager,
}
databasesHandler := &web.DatabasesHandler{
Provider: ts.DiskStorage,
RefreshInterval: 5 * time.Minute,
}
metricsService := &api.MetricsService{
Config: &conf,
TargetManager: targetManager,
Storage: ts,
}
webService := &web.WebService{
StatusHandler: prometheusStatus,
MetricsHandler: metricsService,
DatabasesHandler: databasesHandler,
AlertsHandler: alertsHandler,
}
prometheus := &prometheus{
bodyCompactionTimer: bodyCompactionTimer,
headCompactionTimer: headCompactionTimer,
tailCompactionTimer: tailCompactionTimer,
deletionTimer: deletionTimer,
curationState: prometheusStatus,
curationSema: make(chan bool, 1),
unwrittenSamples: unwrittenSamples,
stopBackgroundOperations: make(chan bool, 1),
Add optional sample replication to OpenTSDB. Prometheus needs long-term storage. Since we don't have enough resources to build our own timeseries storage from scratch ontop of Riak, Cassandra or a similar distributed datastore at the moment, we're planning on using OpenTSDB as long-term storage for Prometheus. It's data model is roughly compatible with that of Prometheus, with some caveats. As a first step, this adds write-only replication from Prometheus to OpenTSDB, with the following things worth noting: 1) I tried to keep the integration lightweight, meaning that anything related to OpenTSDB is isolated to its own package and only main knows about it (essentially it tees all samples to both the existing storage and TSDB). It's not touching the existing TieredStorage at all to avoid more complexity in that area. This might change in the future, especially if we decide to implement a read path for OpenTSDB through Prometheus as well. 2) Backpressure while sending to OpenTSDB is handled by simply dropping samples on the floor when the in-memory queue of samples destined for OpenTSDB runs full. Prometheus also only attempts to send samples once, rather than implementing a complex retry algorithm. Thus, replication to OpenTSDB is best-effort for now. If needed, this may be extended in the future. 3) Samples are sent in batches of limited size to OpenTSDB. The optimal batch size, timeout parameters, etc. may need to be adjusted in the future. 4) OpenTSDB has different rules for legal characters in tag (label) values. While Prometheus allows any characters in label values, OpenTSDB limits them to a to z, A to Z, 0 to 9, -, _, . and /. Currently any illegal characters in Prometheus label values are simply replaced by an underscore. Especially when integrating OpenTSDB with the read path in Prometheus, we'll need to reconsider this: either we'll need to introduce the same limitations for Prometheus labels or escape/encode illegal characters in OpenTSDB in such a way that they are fully decodable again when reading through Prometheus, so that corresponding timeseries in both systems match in their labelsets. Change-Id: I8394c9c55dbac3946a0fa497f566d5e6e2d600b5
11 years ago
ruleManager: ruleManager,
targetManager: targetManager,
notifications: notifications,
storage: ts,
remoteTSDBQueue: remoteTSDBQueue,
}
defer prometheus.close()
storageStarted := make(chan bool)
go ts.Serve(storageStarted)
<-storageStarted
go prometheus.interruptHandler()
go func() {
for _ = range prometheus.headCompactionTimer.C {
glog.Info("Starting head compaction...")
err := prometheus.compact(*headAge, *headGroupSize)
if err != nil {
glog.Error("could not compact: ", err)
}
glog.Info("Done")
}
}()
go func() {
for _ = range prometheus.bodyCompactionTimer.C {
glog.Info("Starting body compaction...")
err := prometheus.compact(*bodyAge, *bodyGroupSize)
if err != nil {
glog.Error("could not compact: ", err)
}
glog.Info("Done")
}
}()
go func() {
for _ = range prometheus.tailCompactionTimer.C {
glog.Info("Starting tail compaction...")
err := prometheus.compact(*tailAge, *tailGroupSize)
if err != nil {
glog.Error("could not compact: ", err)
}
glog.Info("Done")
}
}()
go func() {
for _ = range prometheus.deletionTimer.C {
glog.Info("Starting deletion of stale values...")
err := prometheus.delete(*deleteAge, deletionBatchSize)
if err != nil {
glog.Error("could not delete: ", err)
}
glog.Info("Done")
}
}()
go func() {
err := webService.ServeForever()
if err != nil {
glog.Fatal(err)
}
}()
// TODO(all): Migrate this into prometheus.serve().
for block := range unwrittenSamples {
Add optional sample replication to OpenTSDB. Prometheus needs long-term storage. Since we don't have enough resources to build our own timeseries storage from scratch ontop of Riak, Cassandra or a similar distributed datastore at the moment, we're planning on using OpenTSDB as long-term storage for Prometheus. It's data model is roughly compatible with that of Prometheus, with some caveats. As a first step, this adds write-only replication from Prometheus to OpenTSDB, with the following things worth noting: 1) I tried to keep the integration lightweight, meaning that anything related to OpenTSDB is isolated to its own package and only main knows about it (essentially it tees all samples to both the existing storage and TSDB). It's not touching the existing TieredStorage at all to avoid more complexity in that area. This might change in the future, especially if we decide to implement a read path for OpenTSDB through Prometheus as well. 2) Backpressure while sending to OpenTSDB is handled by simply dropping samples on the floor when the in-memory queue of samples destined for OpenTSDB runs full. Prometheus also only attempts to send samples once, rather than implementing a complex retry algorithm. Thus, replication to OpenTSDB is best-effort for now. If needed, this may be extended in the future. 3) Samples are sent in batches of limited size to OpenTSDB. The optimal batch size, timeout parameters, etc. may need to be adjusted in the future. 4) OpenTSDB has different rules for legal characters in tag (label) values. While Prometheus allows any characters in label values, OpenTSDB limits them to a to z, A to Z, 0 to 9, -, _, . and /. Currently any illegal characters in Prometheus label values are simply replaced by an underscore. Especially when integrating OpenTSDB with the read path in Prometheus, we'll need to reconsider this: either we'll need to introduce the same limitations for Prometheus labels or escape/encode illegal characters in OpenTSDB in such a way that they are fully decodable again when reading through Prometheus, so that corresponding timeseries in both systems match in their labelsets. Change-Id: I8394c9c55dbac3946a0fa497f566d5e6e2d600b5
11 years ago
if block.Err == nil && len(block.Samples) > 0 {
ts.AppendSamples(block.Samples)
Add optional sample replication to OpenTSDB. Prometheus needs long-term storage. Since we don't have enough resources to build our own timeseries storage from scratch ontop of Riak, Cassandra or a similar distributed datastore at the moment, we're planning on using OpenTSDB as long-term storage for Prometheus. It's data model is roughly compatible with that of Prometheus, with some caveats. As a first step, this adds write-only replication from Prometheus to OpenTSDB, with the following things worth noting: 1) I tried to keep the integration lightweight, meaning that anything related to OpenTSDB is isolated to its own package and only main knows about it (essentially it tees all samples to both the existing storage and TSDB). It's not touching the existing TieredStorage at all to avoid more complexity in that area. This might change in the future, especially if we decide to implement a read path for OpenTSDB through Prometheus as well. 2) Backpressure while sending to OpenTSDB is handled by simply dropping samples on the floor when the in-memory queue of samples destined for OpenTSDB runs full. Prometheus also only attempts to send samples once, rather than implementing a complex retry algorithm. Thus, replication to OpenTSDB is best-effort for now. If needed, this may be extended in the future. 3) Samples are sent in batches of limited size to OpenTSDB. The optimal batch size, timeout parameters, etc. may need to be adjusted in the future. 4) OpenTSDB has different rules for legal characters in tag (label) values. While Prometheus allows any characters in label values, OpenTSDB limits them to a to z, A to Z, 0 to 9, -, _, . and /. Currently any illegal characters in Prometheus label values are simply replaced by an underscore. Especially when integrating OpenTSDB with the read path in Prometheus, we'll need to reconsider this: either we'll need to introduce the same limitations for Prometheus labels or escape/encode illegal characters in OpenTSDB in such a way that they are fully decodable again when reading through Prometheus, so that corresponding timeseries in both systems match in their labelsets. Change-Id: I8394c9c55dbac3946a0fa497f566d5e6e2d600b5
11 years ago
if remoteTSDBQueue != nil {
remoteTSDBQueue.Queue(block.Samples)
}
}
}
}