1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180 181 182 183 184 185 186 187 188 189 190 191 192 193 194 195 196 197 198 199 200 201 202 203 204 205 206 207 208 209 210 211 212 213 214 215 216 217 218 219 220 221 222 223 224 225 226 227 228 229 230 231 232 233 234 235 236 237 238 239 240 241 242 243 244 245 246 247 248 249 250 251 252 253 254 255 256 257 258 259 260 261 262 263 264 265 266 267 268 269 270 271 272 273 274 275 276 277 278 279 280 281 282 283 284 285 286 287 288 289 290 291 292 293 294 295 296 297 298 299 300 301 302 303 304 305 306 307 308 309 310 311 312 313 314 315 316 317 318 319 320 321 322 323 324 325 326 327 328 329 330 331 332 333 334 335 336 337 338 339 340 341 342 343 344 345 346 347 348 349 350 351 352 353 354 355 356 357 358 359 360 361 362 363 364 365 366 367 368 369 370 371 372 373 374 375 376 377 378 379 380 381 382 383 384 385 386 387 388 389 390 391 392 393 394 395 396 397 398 399 400 401 402 403 404 405
|
// Package dogstatsd provides a DogStatsD backend for package metrics. It's very
// similar to StatsD, but supports arbitrary tags per-metric, which map to Go
// kit's label values. So, while label values are no-ops in StatsD, they are
// supported here. For more details, see the documentation at
// http://docs.datadoghq.com/guides/dogstatsd/.
//
// This package batches observations and emits them on some schedule to the
// remote server. This is useful even if you connect to your DogStatsD server
// over UDP. Emitting one network packet per observation can quickly overwhelm
// even the fastest internal network.
package dogstatsd
import (
"context"
"fmt"
"io"
"math/rand"
"strings"
"sync"
"sync/atomic"
"time"
"github.com/go-kit/kit/metrics"
"github.com/go-kit/kit/metrics/generic"
"github.com/go-kit/kit/metrics/internal/lv"
"github.com/go-kit/kit/metrics/internal/ratemap"
"github.com/go-kit/kit/util/conn"
"github.com/go-kit/log"
)
// Dogstatsd receives metrics observations and forwards them to a DogStatsD
// server. Create a Dogstatsd object, use it to create metrics, and pass those
// metrics as dependencies to the components that will use them.
//
// All metrics are buffered until WriteTo is called. Counters and gauges are
// aggregated into a single observation per timeseries per write. Timings and
// histograms are buffered but not aggregated.
//
// To regularly report metrics to an io.Writer, use the WriteLoop helper method.
// To send to a DogStatsD server, use the SendLoop helper method.
type Dogstatsd struct {
mtx sync.RWMutex
prefix string
rates *ratemap.RateMap
counters *lv.Space
gauges map[string]*gaugeNode
timings *lv.Space
histograms *lv.Space
logger log.Logger
lvs lv.LabelValues
}
// New returns a Dogstatsd object that may be used to create metrics. Prefix is
// applied to all created metrics. Callers must ensure that regular calls to
// WriteTo are performed, either manually or with one of the helper methods.
func New(prefix string, logger log.Logger, lvs ...string) *Dogstatsd {
if len(lvs)%2 != 0 {
panic("odd number of LabelValues; programmer error!")
}
return &Dogstatsd{
prefix: prefix,
rates: ratemap.New(),
counters: lv.NewSpace(),
gauges: map[string]*gaugeNode{},
timings: lv.NewSpace(),
histograms: lv.NewSpace(),
logger: logger,
lvs: lvs,
}
}
// NewCounter returns a counter, sending observations to this Dogstatsd object.
func (d *Dogstatsd) NewCounter(name string, sampleRate float64) *Counter {
d.rates.Set(name, sampleRate)
return &Counter{
name: name,
obs: sampleObservations(d.counters.Observe, sampleRate),
}
}
// NewGauge returns a gauge, sending observations to this Dogstatsd object.
func (d *Dogstatsd) NewGauge(name string) *Gauge {
d.mtx.Lock()
n, ok := d.gauges[name]
if !ok {
n = &gaugeNode{gauge: &Gauge{g: generic.NewGauge(name), ddog: d}}
d.gauges[name] = n
}
d.mtx.Unlock()
return n.gauge
}
// NewTiming returns a histogram whose observations are interpreted as
// millisecond durations, and are forwarded to this Dogstatsd object.
func (d *Dogstatsd) NewTiming(name string, sampleRate float64) *Timing {
d.rates.Set(name, sampleRate)
return &Timing{
name: name,
obs: sampleObservations(d.timings.Observe, sampleRate),
}
}
// NewHistogram returns a histogram whose observations are of an unspecified
// unit, and are forwarded to this Dogstatsd object.
func (d *Dogstatsd) NewHistogram(name string, sampleRate float64) *Histogram {
d.rates.Set(name, sampleRate)
return &Histogram{
name: name,
obs: sampleObservations(d.histograms.Observe, sampleRate),
}
}
// WriteLoop is a helper method that invokes WriteTo to the passed writer every
// time the passed channel fires. This method blocks until ctx is canceled,
// so clients probably want to run it in its own goroutine. For typical
// usage, create a time.Ticker and pass its C channel to this method.
func (d *Dogstatsd) WriteLoop(ctx context.Context, c <-chan time.Time, w io.Writer) {
for {
select {
case <-c:
if _, err := d.WriteTo(w); err != nil {
d.logger.Log("during", "WriteTo", "err", err)
}
case <-ctx.Done():
return
}
}
}
// SendLoop is a helper method that wraps WriteLoop, passing a managed
// connection to the network and address. Like WriteLoop, this method blocks
// until ctx is canceled, so clients probably want to start it in its own
// goroutine. For typical usage, create a time.Ticker and pass its C channel to
// this method.
func (d *Dogstatsd) SendLoop(ctx context.Context, c <-chan time.Time, network, address string) {
d.WriteLoop(ctx, c, conn.NewDefaultManager(network, address, d.logger))
}
// WriteTo flushes the buffered content of the metrics to the writer, in
// DogStatsD format. WriteTo abides best-effort semantics, so observations are
// lost if there is a problem with the write. Clients should be sure to call
// WriteTo regularly, ideally through the WriteLoop or SendLoop helper methods.
func (d *Dogstatsd) WriteTo(w io.Writer) (count int64, err error) {
var n int
d.counters.Reset().Walk(func(name string, lvs lv.LabelValues, values []float64) bool {
n, err = fmt.Fprintf(w, "%s%s:%f|c%s%s\n", d.prefix, name, sum(values), sampling(d.rates.Get(name)), d.tagValues(lvs))
if err != nil {
return false
}
count += int64(n)
return true
})
if err != nil {
return count, err
}
d.mtx.RLock()
for _, root := range d.gauges {
root.walk(func(name string, lvs lv.LabelValues, value float64) bool {
n, err = fmt.Fprintf(w, "%s%s:%f|g%s\n", d.prefix, name, value, d.tagValues(lvs))
if err != nil {
return false
}
count += int64(n)
return true
})
}
d.mtx.RUnlock()
d.timings.Reset().Walk(func(name string, lvs lv.LabelValues, values []float64) bool {
sampleRate := d.rates.Get(name)
for _, value := range values {
n, err = fmt.Fprintf(w, "%s%s:%f|ms%s%s\n", d.prefix, name, value, sampling(sampleRate), d.tagValues(lvs))
if err != nil {
return false
}
count += int64(n)
}
return true
})
if err != nil {
return count, err
}
d.histograms.Reset().Walk(func(name string, lvs lv.LabelValues, values []float64) bool {
sampleRate := d.rates.Get(name)
for _, value := range values {
n, err = fmt.Fprintf(w, "%s%s:%f|h%s%s\n", d.prefix, name, value, sampling(sampleRate), d.tagValues(lvs))
if err != nil {
return false
}
count += int64(n)
}
return true
})
if err != nil {
return count, err
}
return count, err
}
func sum(a []float64) float64 {
var v float64
for _, f := range a {
v += f
}
return v
}
func sampling(r float64) string {
var sv string
if r < 1.0 {
sv = fmt.Sprintf("|@%f", r)
}
return sv
}
func (d *Dogstatsd) tagValues(labelValues []string) string {
if len(labelValues) == 0 && len(d.lvs) == 0 {
return ""
}
if len(labelValues)%2 != 0 {
panic("tagValues received a labelValues with an odd number of strings")
}
pairs := make([]string, 0, (len(d.lvs)+len(labelValues))/2)
for i := 0; i < len(d.lvs); i += 2 {
pairs = append(pairs, d.lvs[i]+":"+d.lvs[i+1])
}
for i := 0; i < len(labelValues); i += 2 {
pairs = append(pairs, labelValues[i]+":"+labelValues[i+1])
}
return "|#" + strings.Join(pairs, ",")
}
type observeFunc func(name string, lvs lv.LabelValues, value float64)
// sampleObservations returns a modified observeFunc that samples observations.
func sampleObservations(obs observeFunc, sampleRate float64) observeFunc {
if sampleRate >= 1 {
return obs
}
return func(name string, lvs lv.LabelValues, value float64) {
if rand.Float64() > sampleRate {
return
}
obs(name, lvs, value)
}
}
// Counter is a DogStatsD counter. Observations are forwarded to a Dogstatsd
// object, and aggregated (summed) per timeseries.
type Counter struct {
name string
lvs lv.LabelValues
obs observeFunc
}
// With implements metrics.Counter.
func (c *Counter) With(labelValues ...string) metrics.Counter {
return &Counter{
name: c.name,
lvs: c.lvs.With(labelValues...),
obs: c.obs,
}
}
// Add implements metrics.Counter.
func (c *Counter) Add(delta float64) {
c.obs(c.name, c.lvs, delta)
}
// Gauge is a DogStatsD gauge. Observations are forwarded to a Dogstatsd
// object, and aggregated (the last observation selected) per timeseries.
type Gauge struct {
g *generic.Gauge
ddog *Dogstatsd
set int32
}
// With implements metrics.Gauge.
func (g *Gauge) With(labelValues ...string) metrics.Gauge {
g.ddog.mtx.RLock()
node := g.ddog.gauges[g.g.Name]
g.ddog.mtx.RUnlock()
ga := &Gauge{g: g.g.With(labelValues...).(*generic.Gauge), ddog: g.ddog}
return node.addGauge(ga, ga.g.LabelValues())
}
// Set implements metrics.Gauge.
func (g *Gauge) Set(value float64) {
g.g.Set(value)
g.touch()
}
// Add implements metrics.Gauge.
func (g *Gauge) Add(delta float64) {
g.g.Add(delta)
g.touch()
}
// Timing is a DogStatsD timing, or metrics.Histogram. Observations are
// forwarded to a Dogstatsd object, and collected (but not aggregated) per
// timeseries.
type Timing struct {
name string
lvs lv.LabelValues
obs observeFunc
}
// With implements metrics.Timing.
func (t *Timing) With(labelValues ...string) metrics.Histogram {
return &Timing{
name: t.name,
lvs: t.lvs.With(labelValues...),
obs: t.obs,
}
}
// Observe implements metrics.Histogram. Value is interpreted as milliseconds.
func (t *Timing) Observe(value float64) {
t.obs(t.name, t.lvs, value)
}
// Histogram is a DogStatsD histrogram. Observations are forwarded to a
// Dogstatsd object, and collected (but not aggregated) per timeseries.
type Histogram struct {
name string
lvs lv.LabelValues
obs observeFunc
}
// With implements metrics.Histogram.
func (h *Histogram) With(labelValues ...string) metrics.Histogram {
return &Histogram{
name: h.name,
lvs: h.lvs.With(labelValues...),
obs: h.obs,
}
}
// Observe implements metrics.Histogram.
func (h *Histogram) Observe(value float64) {
h.obs(h.name, h.lvs, value)
}
type pair struct{ label, value string }
type gaugeNode struct {
mtx sync.RWMutex
gauge *Gauge
children map[pair]*gaugeNode
}
func (n *gaugeNode) addGauge(g *Gauge, lvs lv.LabelValues) *Gauge {
n.mtx.Lock()
defer n.mtx.Unlock()
if len(lvs) == 0 {
if n.gauge == nil {
n.gauge = g
}
return n.gauge
}
if len(lvs) < 2 {
panic("too few LabelValues; programmer error!")
}
head, tail := pair{lvs[0], lvs[1]}, lvs[2:]
if n.children == nil {
n.children = map[pair]*gaugeNode{}
}
child, ok := n.children[head]
if !ok {
child = &gaugeNode{}
n.children[head] = child
}
return child.addGauge(g, tail)
}
func (n *gaugeNode) walk(fn func(string, lv.LabelValues, float64) bool) bool {
n.mtx.RLock()
defer n.mtx.RUnlock()
if n.gauge != nil {
value, ok := n.gauge.read()
if ok && !fn(n.gauge.g.Name, n.gauge.g.LabelValues(), value) {
return false
}
}
for _, child := range n.children {
if !child.walk(fn) {
return false
}
}
return true
}
func (g *Gauge) touch() {
atomic.StoreInt32(&(g.set), 1)
}
func (g *Gauge) read() (float64, bool) {
set := atomic.SwapInt32(&(g.set), 0)
return g.g.Value(), set != 0
}
|