statsd metric specification document
gorets:1|c
This is a simple counter. Add 1 to the "gorets" bucket.
At each flush the current count is sent and reset to 0.
If the count at flush is 0 then you can opt to send no metric at all for
this counter, by setting config.deleteCounters
(applies only to graphite
backend). Statsd will send both the rate as well as the count at each flush.
gorets:1|c|@0.1
Tells StatsD that this counter is being sent sampled every 1/10th of the time.
glork:320|ms
The glork took 320ms to complete this time. StatsD figures out percentiles,
average (mean), standard deviation, sum, lower and upper bounds for the flush interval.
The percentile threshold can be tweaked with config.percentThreshold
.
The percentile threshold can be a single value, or a list of values, and will generate the following list of stats for each threshold:
stats.timers.$KEY.mean_$PCT
stats.timers.$KEY.upper_$PCT
stats.timers.$KEY.sum_$PCT
Where $KEY
is the stats key you specify when sending to statsd, and $PCT
is
the percentile threshold.
Note that the mean
metric is the mean value of all timings recorded during
the flush interval whereas mean_$PCT
is the mean of all timings which fell
into the $PCT
percentile for that flush interval. And the same holds for sum
and upper. See issue #157 for a
more detailed explanation of the calculation.
If the count at flush is 0 then you can opt to send no metric at all for this timer,
by setting config.deleteTimers
.
Use the config.histogram
setting to instruct statsd to maintain histograms
over time. Specify which metrics to match and a corresponding list of
ordered non-inclusive upper limits of bins (class intervals).
(use inf
to denote infinity; a lower limit of 0 is assumed)
Each flushInterval
, statsd will store how many values (absolute frequency)
fall within each bin (class interval), for all matching metrics.
Examples:
no histograms for any timer (default): []
histogram to only track render durations, with unequal class intervals and catchall for outliers:
[ { metric: 'render', bins: [ 0.01, 0.1, 1, 10, 'inf'] } ]
histogram for all timers except 'foo' related, with equal class interval and catchall for outliers:
[ { metric: 'foo', bins: [] },
{ metric: '', bins: [ 50, 100, 150, 200, 'inf'] } ]
Note:
StatsD now also supports gauges, arbitrary values, which can be recorded.
gaugor:333|g
If the gauge is not updated at the next flush, it will send the previous value. You can opt to send
no metric at all for this gauge, by setting config.deleteGauge
Adding a sign to the gauge value will change the value, rather than setting it.
gaugor:-10|g
gaugor:+4|g
So if gaugor
was 333
, those commands would set it to 333 - 10 + 4
, or
327
.
Note:
This implies you can't explicitly set a gauge to a negative number without first setting it to zero.
StatsD supports counting unique occurences of events between flushes, using a Set to store all occuring events.
uniques:765|s
If the count at flush is 0 then you can opt to send no metric at all for this set, by
setting config.deleteSets
.
StatsD supports receiving multiple metrics in a single packet by separating them with a newline.
gorets:1|c\nglork:320|ms\ngaugor:333|g\nuniques:765|s
Be careful to keep the total length of the payload within your network's MTU. There is no single good value to use, but here are some guidelines for common network scenarios:
(These payload numbers take into account the maximum IP + UDP header sizes)