A network daemon for aggregating statistics (counters and timers), rolling them up, then sending them to graphite.
We (Etsy) blogged about how it works and why we created it.
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buckets Each stat is in it's own "bucket". They are not predefined anywhere. Buckets can be named anything that will translate to Graphite (periods make folders, etc)
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values Each stat will have a value. How it is interpreted depends on modifiers
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flush After the flush interval timeout (default 10 seconds), stats are munged and sent over to Graphite.
gorets:5|v
This is a simple pass-thru value. By default, it forwards the last value submitted during the interval to carbon. It looks like a UDP-to-TCP bridge. This modifier accepts a number of additionnal (optionnal) flags:
last: the default, it means that only the last value submitted during the interval is submitted
first: sends the first value submitted during the interval (ignoring the others)
min: sends the min value submitted during the interval
max: sends the max value submitted during the interval
avg: sends the average of the values submitted during the interval
Example:
pouf:5|v|avg
gorets:1|c
This is a simple counter. Add 1 to the "gorets" bucket. It stays in memory until the flush interval.
glork:320|ms
The glork took 320ms to complete this time. StatsD figures out 90th percentile, average (mean), lower and upper bounds for the flush interval.
gorets:1|c|@0.1
Tells StatsD that this counter is being sent sampled every 1/10th of the time.
Graphite uses "schemas" to define the different round robin datasets it houses (analogous to RRAs in rrdtool). Here's what Etsy is using for the stats databases:
[stats]
priority = 110
pattern = ^stats\..*
retentions = 10:2160,60:10080,600:262974
That translates to:
- 6 hours of 10 second data (what we consider "near-realtime")
- 1 week of 1 minute data
- 5 years of 10 minute data
This has been a good tradeoff so far between size-of-file (round robin databases are fixed size) and data we care about. Each "stats" database is about 3.2 megs with these retentions.
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Install node.js
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Clone the project
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Create a config file from exampleConfig.js and put it somewhere
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Start the Daemon:
node stats.js /path/to/config
StatsD was inspired (heavily) by the project (of the same name) at Flickr. Here's a post where Cal Henderson described it in depth: Counting and timing. Cal re-released the code recently: Perl StatsD
You're interested in contributing to StatsD? AWESOME. Here are the basic steps:
fork StatsD from here: http://github.com/etsy/statsd
- Clone your fork
- Hack away
- If you are adding new functionality, document it in the README
- If necessary, rebase your commits into logical chunks, without errors
- Push the branch up to GitHub
- Send a pull request to the etsy/statsd project.
We'll do our best to get your changes in!
In lieu of a list of contributors, check out the commit history for the project: http://github.com/etsy/statsd/commits/master