statsd-influxdb-furu v0.5.1
StatsD InfluxDB backend
Fork of https://github.com/bernd/statsd-influxdb-backend to support SET
and continue maintenance. furu
means full in Japanese.
A naive InfluxDB backend for StatsD.
It can ship events to InfluxDB using two different strategies which can be used at the same time.
Regular Flush Strategy
StatsD will flush aggregated metrics with a configured interval. This is the regular StatsD mode of operation.
Proxy Strategy
This will map every incoming StatsD packet to an InfluxDB event. It's useful if you want to store the raw events in InfluxDB without any rollups.
CAVEATS
This is pretty young and I do not have much experience with InfluxDB yet. Especially the event buffering and the event mapping might be problematic and inefficient.
InfluxDB is also pretty young and there might be breaking changes until it reaches 1.0.
Please be careful!
Installation
$ cd /path/to/statsd
$ npm install statsd-influxdb-furu
Configuration
You can configure the following settings in your StatsD config file.
{
graphitePort: 2003,
graphiteHost: "graphite.example.com",
port: 8125,
backends: [ "./backends/graphite", "statsd-influxdb-furu" ],
influxdb: {
host: '127.0.0.1', // InfluxDB host. (default 127.0.0.1)
port: 8086, // InfluxDB port. (default 8086)
ssl: false, // InfluxDB is hosted over SSL. (default false)
database: 'dbname', // InfluxDB database instance. (required)
username: 'user', // InfluxDB database username. (required)
password: 'pass', // InfluxDB database password. (required)
flush: {
enable: true // Enable regular flush strategy. (default true)
},
proxy: {
enable: false, // Enable the proxy strategy. (default false)
suffix: 'raw', // Metric name suffix. (default 'raw')
flushInterval: 1000 // Flush interval for the internal buffer.
// (default 1000)
}
}
}
Activation
Add the statsd-influxdb-backend
to the list of StatsD backends in the config
file and restart the StatsD process.
{
backends: ['./backends/graphite', 'statsd-influxdb-backend']
}
Unsupported Metric Types
Proxy Strategy
- Counter with sampling.
- Signed gauges. (i.e.
bytes:+4|g
) - Sets
InfluxDB Event Mapping
StatsD packets are currently mapped to the following InfluxDB events. This is a first try and I'm open to suggestions to improve this.
Set
StatsD package client_version:1.1|c
, client_version:1.2|c
as Influx event:
[
{
name: 'visior',
columns: ['value', 'time'],
points: [['1.1', 1384798553000], ['1.2', 1384798553001]]
}
]
If you are using Grafana to visualize a Set, then using this query or something similar
SELECT version, count(version) FROM client_version GROUP BY version, time(1m)
Also, to count for the size of unique value, another InfluxDB event is also pushed
[
{
name: 'visitor_count',
columns: ['value', 'time'],
points: [set.length, 1384798553001]
}
]
Counter
StatsD packet requests:1|c
as InfluxDB event:
Flush Strategy
[
{
name: 'requests.counter',
columns: ['value', 'time'],
points: [[802, 1384798553000]]
}
]
Proxy Strategy
[
{
name: 'requests.counter.raw',
columns: ['value', 'time'],
points: [[1, 1384472029572]]
}
]
Timing
StatsD packet response_time:170|ms
as InfluxDB event:
Flush Strategy
[
{
name: 'response_time.timer.mean_90',
columns: ['value', 'time'],
points: [[445.25761772853184, 1384798553000]]
},
{
name: 'response_time.timer.upper_90',
columns: ['value', 'time'],
points: [[905, 1384798553000]]
},
{
name: 'response_time.timer.sum_90',
columns: ['value', 'time'],
points: [[321476, 1384798553000]]
},
{
name: 'response_time.timer.std',
columns: ['value', 'time'],
points: [[294.4171159604542, 1384798553000]]
},
{
name: 'response_time.timer.upper',
columns: ['value', 'time'],
points: [[998, 1384798553000]]
},
{
name: 'response_time.timer.lower',
columns: ['value', 'time'],
points: [[2, 1384798553000]]
},
{
name: 'response_time.timer.count',
columns: ['value', 'time'],
points: [[802, 1384798553000]]
},
{
name: 'response_time.timer.count_ps',
columns: ['value', 'time'],
points: [[80.2, 1384798553000]]
},
{
name: 'response_time.timer.sum',
columns: ['value', 'time'],
points: [[397501, 1384798553000]]
},
{
name: 'response_time.timer.mean',
columns: ['value', 'time'],
points: [[495.6371571072319, 1384798553000]]
},
{
name: 'response_time.timer.median',
columns: ['value', 'time'],
points: [[483, 1384798553000]]
}
]
Proxy Strategy
[
{
name: 'response_time.timer.raw',
columns: ['value', 'time'],
points: [[170, 1384472029572]]
}
]
Gauges
StatsD packet bytes:123|g
as InfluxDB event:
Flush Strategy
[
{
name: 'bytes.gauge',
columns: ['value', 'time'],
points: [[123, 1384798553000]]
}
]
Proxy Strategy
[
{
name: 'bytes.gauge.raw',
columns: ['value', 'time'],
points: [['gauge', 123, 1384472029572]]
}
]
Proxy Strategy Notes
Event Buffering
To avoid one HTTP request per StatsD packet, the InfluxDB backend buffers the
incoming events and flushes the buffer on a regular basis. The current default
is 1000ms. Use the influxdb.proxy.flushInterval
to change the interval.
This might become a problem with lots of incoming events.
The payload of a HTTP request might look like this:
[
{
name: 'requests.counter.raw',
columns: ['value', 'time'],
points: [
[1, 1384472029572],
[1, 1384472029573],
[1, 1384472029580]
]
},
{
name: 'response_time.timer.raw',
columns: ['value', 'time'],
points: [
[170, 1384472029570],
[189, 1384472029572],
[234, 1384472029578],
[135, 1384472029585]
]
},
{
name: 'bytes.gauge.raw',
columns: ['value', 'time'],
points: [
[123, 1384472029572],
[123, 1384472029580]
]
}
]
Contributing
All contributions are welcome: ideas, patches, documentation, bug reports, complaints, and even something you drew up on a napkin.