Telegraf Service Plugin: statsd
# Statsd Server [[inputs.statsd]] ## Protocol, must be "tcp", "udp4", "udp6" or "udp" (default=udp) protocol = "udp" ## MaxTCPConnection - applicable when protocol is set to tcp (default=250) max_tcp_connections = 250 ## Enable TCP keep alive probes (default=false) tcp_keep_alive = false ## Specifies the keep-alive period for an active network connection. ## Only applies to TCP sockets and will be ignored if tcp_keep_alive is false. ## Defaults to the OS configuration. # tcp_keep_alive_period = "2h" ## Address and port to host UDP listener on service_address = ":8125" ## The following configuration options control when telegraf clears it's cache ## of previous values. If set to false, then telegraf will only clear it's ## cache when the daemon is restarted. ## Reset gauges every interval (default=true) delete_gauges = true ## Reset counters every interval (default=true) delete_counters = true ## Reset sets every interval (default=true) delete_sets = true ## Reset timings & histograms every interval (default=true) delete_timings = true ## Percentiles to calculate for timing & histogram stats percentiles =  ## separator to use between elements of a statsd metric metric_separator = "_" ## Parses tags in the datadog statsd format ## http://docs.datadoghq.com/guides/dogstatsd/ parse_data_dog_tags = false ## Statsd data translation templates, more info can be read here: ## https://github.com/influxdata/telegraf/blob/master/docs/DATA_FORMATS_INPUT.md#graphite # templates = [ # "cpu.* measurement*" # ] ## Number of UDP messages allowed to queue up, once filled, ## the statsd server will start dropping packets allowed_pending_messages = 10000 ## Number of timing/histogram values to track per-measurement in the ## calculation of percentiles. Raising this limit increases the accuracy ## of percentiles but also increases the memory usage and cpu time. percentile_limit = 1000
The statsd plugin is a special type of plugin which runs a backgrounded statsd listener service while telegraf is running.
The format of the statsd messages was based on the format described in the original etsy statsd implementation. In short, the telegraf statsd listener will accept:
deploys.test.myservice:1|c<- increments by 1
deploys.test.myservice:101|c<- increments by 101
deploys.test.myservice:firstname.lastname@example.org<- with sample rate, increments by 10
users.unique:102|s<- would result in a count of 2 for
- Timings & Histograms
load.time:email@example.com<- sampled 1/10 of the time
It is possible to omit repetitive names and merge individual stats into a single line by separating them with additional colons:
This also allows for mixed types in a single line:
foo:1|c:200|ms is internally split into two individual metrics
foo:200|ms which are added to the aggregator separately.
In order to take advantage of InfluxDB's tagging system, we have made a couple additions to the standard statsd protocol. First, you can specify tags in a manner similar to the line-protocol, like this:
Outputted measurements will depend entirely on the measurements that the user sends, but here is a brief rundown of what you can expect to find from each metric type:
- Gauges are a constant data type. They are not subject to averaging, and they don’t change unless you change them. That is, once you set a gauge value, it will be a flat line on the graph until you change it again.
- Counters are the most basic type. They are treated as a count of a type of
event. They will continually increase unless you set
- Counters are the most basic type. They are treated as a count of a type of event. They will continually increase unless you set
- Sets count the number of unique values passed to a key. For example, you
could count the number of users accessing your system using
users:<user_id>|s. No matter how many times the same user_id is sent, the count will only increase by 1.
- Sets count the number of unique values passed to a key. For example, you could count the number of users accessing your system using
- Timings & Histograms
- Timers are meant to track how long something took. They are an invaluable tool for tracking application performance.
- The following aggregate measurements are made for timers:
statsd_<name>_lower: The lower bound is the lowest value statsd saw for that stat during that interval.
statsd_<name>_upper: The upper bound is the highest value statsd saw for that stat during that interval.
statsd_<name>_mean: The mean is the average of all values statsd saw for that stat during that interval.
statsd_<name>_stddev: The stddev is the sample standard deviation of all values statsd saw for that stat during that interval.
statsd_<name>_sum: The sum is the sample sum of all values statsd saw for that stat during that interval.
statsd_<name>_count: The count is the number of timings statsd saw for that stat during that interval. It is not averaged.
Pthpercentile is a value x such that
P%of all the values statsd saw for that stat during that time period are below x. The most common value that people use for
90, this is a great number to try to optimize.
- protocol string: Protocol used in listener - tcp or udp options
- max_tcp_connections int: Maximum number of concurrent TCP connections to allow. Used when protocol is set to tcp.
- tcp_keep_alive boolean: Enable TCP keep alive probes
- tcp_keep_alive_period internal.Duration: Specifies the keep-alive period for an active network connection
- service_address string: Address to listen for statsd UDP packets on
- delete_gauges boolean: Delete gauges on every collection interval
- delete_counters boolean: Delete counters on every collection interval
- delete_sets boolean: Delete set counters on every collection interval
- delete_timings boolean: Delete timings on every collection interval
- percentiles int: Percentiles to calculate for timing & histogram stats
- allowed_pending_messages integer: Number of messages allowed to queue up waiting to be processed. When this fills, messages will be dropped and logged.
- percentile_limit integer: Number of timing/histogram values to track per-measurement in the calculation of percentiles. Raising this limit increases the accuracy of percentiles but also increases the memory usage and cpu time.
- templates string: Templates for transforming statsd buckets into influx measurements and tags.
- parse_data_dog_tags boolean: Enable parsing of tags in DataDog's dogstatsd format (http://docs.datadoghq.com/guides/dogstatsd/)
Statsd bucket -> InfluxDB line-protocol Templates
The plugin supports specifying templates for transforming statsd buckets into InfluxDB measurement names and tags. The templates have a measurement keyword, which can be used to specify parts of the bucket that are to be used in the measurement name. Other words in the template are used as tag names. For example, the following template:
templates = [ "measurement.measurement.region" ]
would result in the following transformation:
cpu.load.us-west:100|g => cpu_load,region=us-west 100
Users can also filter the template to use based on the name of the bucket, using glob matching, like so:
templates = [ "cpu.* measurement.measurement.region", "mem.* measurement.measurement.host" ]
which would result in the following transformation:
cpu.load.us-west:100|g => cpu_load,region=us-west 100 mem.cached.localhost:256|g => mem_cached,host=localhost 256
There are many more options available, More details can be found here