232 lines
8.8 KiB
Markdown
232 lines
8.8 KiB
Markdown
# Telegraf Service Plugin: statsd
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### Configuration
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```toml
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# Statsd Server
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[[inputs.statsd]]
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## Protocol, must be "tcp", "udp4", "udp6" or "udp" (default=udp)
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protocol = "udp"
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## MaxTCPConnection - applicable when protocol is set to tcp (default=250)
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max_tcp_connections = 250
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## Enable TCP keep alive probes (default=false)
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tcp_keep_alive = false
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## Specifies the keep-alive period for an active network connection.
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## Only applies to TCP sockets and will be ignored if tcp_keep_alive is false.
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## Defaults to the OS configuration.
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# tcp_keep_alive_period = "2h"
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## Address and port to host UDP listener on
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service_address = ":8125"
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## The following configuration options control when telegraf clears it's cache
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## of previous values. If set to false, then telegraf will only clear it's
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## cache when the daemon is restarted.
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## Reset gauges every interval (default=true)
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delete_gauges = true
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## Reset counters every interval (default=true)
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delete_counters = true
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## Reset sets every interval (default=true)
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delete_sets = true
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## Reset timings & histograms every interval (default=true)
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delete_timings = true
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## Percentiles to calculate for timing & histogram stats
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percentiles = [90]
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## separator to use between elements of a statsd metric
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metric_separator = "_"
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## Parses tags in the datadog statsd format
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## http://docs.datadoghq.com/guides/dogstatsd/
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parse_data_dog_tags = false
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## Statsd data translation templates, more info can be read here:
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## https://github.com/influxdata/telegraf/blob/master/docs/DATA_FORMATS_INPUT.md#graphite
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# templates = [
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# "cpu.* measurement*"
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# ]
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## Number of UDP messages allowed to queue up, once filled,
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## the statsd server will start dropping packets
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allowed_pending_messages = 10000
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## Number of timing/histogram values to track per-measurement in the
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## calculation of percentiles. Raising this limit increases the accuracy
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## of percentiles but also increases the memory usage and cpu time.
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percentile_limit = 1000
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## Maximum socket buffer size in bytes, once the buffer fills up, metrics
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## will start dropping. Defaults to the OS default.
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# read_buffer_size = 65535
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```
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### Description
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The statsd plugin is a special type of plugin which runs a backgrounded statsd
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listener service while telegraf is running.
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The format of the statsd messages was based on the format described in the
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original [etsy statsd](https://github.com/etsy/statsd/blob/master/docs/metric_types.md)
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implementation. In short, the telegraf statsd listener will accept:
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- Gauges
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- `users.current.den001.myapp:32|g` <- standard
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- `users.current.den001.myapp:+10|g` <- additive
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- `users.current.den001.myapp:-10|g`
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- Counters
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- `deploys.test.myservice:1|c` <- increments by 1
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- `deploys.test.myservice:101|c` <- increments by 101
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- `deploys.test.myservice:1|c|@0.1` <- with sample rate, increments by 10
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- Sets
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- `users.unique:101|s`
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- `users.unique:101|s`
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- `users.unique:102|s` <- would result in a count of 2 for `users.unique`
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- Timings & Histograms
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- `load.time:320|ms`
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- `load.time.nanoseconds:1|h`
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- `load.time:200|ms|@0.1` <- sampled 1/10 of the time
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It is possible to omit repetitive names and merge individual stats into a
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single line by separating them with additional colons:
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- `users.current.den001.myapp:32|g:+10|g:-10|g`
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- `deploys.test.myservice:1|c:101|c:1|c|@0.1`
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- `users.unique:101|s:101|s:102|s`
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- `load.time:320|ms:200|ms|@0.1`
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This also allows for mixed types in a single line:
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- `foo:1|c:200|ms`
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The string `foo:1|c:200|ms` is internally split into two individual metrics
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`foo:1|c` and `foo:200|ms` which are added to the aggregator separately.
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### Influx Statsd
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In order to take advantage of InfluxDB's tagging system, we have made a couple
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additions to the standard statsd protocol. First, you can specify
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tags in a manner similar to the line-protocol, like this:
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```
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users.current,service=payroll,region=us-west:32|g
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```
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<!-- TODO Second, you can specify multiple fields within a measurement:
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```
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current.users,service=payroll,server=host01:west=10,east=10,central=2,south=10|g
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``` -->
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### Measurements:
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Meta:
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- tags: `metric_type=<gauge|set|counter|timing|histogram>`
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Outputted measurements will depend entirely on the measurements that the user
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sends, but here is a brief rundown of what you can expect to find from each
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metric type:
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- Gauges
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- Gauges are a constant data type. They are not subject to averaging, and they
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don’t change unless you change them. That is, once you set a gauge value, it
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will be a flat line on the graph until you change it again.
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- Counters
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- Counters are the most basic type. They are treated as a count of a type of
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event. They will continually increase unless you set `delete_counters=true`.
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- Sets
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- Sets count the number of unique values passed to a key. For example, you
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could count the number of users accessing your system using `users:<user_id>|s`.
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No matter how many times the same user_id is sent, the count will only increase
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by 1.
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- Timings & Histograms
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- Timers are meant to track how long something took. They are an invaluable
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tool for tracking application performance.
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- The following aggregate measurements are made for timers:
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- `statsd_<name>_lower`: The lower bound is the lowest value statsd saw
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for that stat during that interval.
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- `statsd_<name>_upper`: The upper bound is the highest value statsd saw
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for that stat during that interval.
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- `statsd_<name>_mean`: The mean is the average of all values statsd saw
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for that stat during that interval.
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- `statsd_<name>_stddev`: The stddev is the sample standard deviation
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of all values statsd saw for that stat during that interval.
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- `statsd_<name>_sum`: The sum is the sample sum of all values statsd saw
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for that stat during that interval.
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- `statsd_<name>_count`: The count is the number of timings statsd saw
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for that stat during that interval. It is not averaged.
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- `statsd_<name>_percentile_<P>` The `Pth` percentile is a value x such
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that `P%` of all the values statsd saw for that stat during that time
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period are below x. The most common value that people use for `P` is the
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`90`, this is a great number to try to optimize.
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### Plugin arguments
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- **protocol** string: Protocol used in listener - tcp or udp options
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- **max_tcp_connections** []int: Maximum number of concurrent TCP connections
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to allow. Used when protocol is set to tcp.
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- **tcp_keep_alive** boolean: Enable TCP keep alive probes
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- **tcp_keep_alive_period** internal.Duration: Specifies the keep-alive period for an active network connection
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- **service_address** string: Address to listen for statsd UDP packets on
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- **delete_gauges** boolean: Delete gauges on every collection interval
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- **delete_counters** boolean: Delete counters on every collection interval
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- **delete_sets** boolean: Delete set counters on every collection interval
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- **delete_timings** boolean: Delete timings on every collection interval
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- **percentiles** []int: Percentiles to calculate for timing & histogram stats
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- **allowed_pending_messages** integer: Number of messages allowed to queue up
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waiting to be processed. When this fills, messages will be dropped and logged.
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- **percentile_limit** integer: Number of timing/histogram values to track
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per-measurement in the calculation of percentiles. Raising this limit increases
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the accuracy of percentiles but also increases the memory usage and cpu time.
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- **templates** []string: Templates for transforming statsd buckets into influx
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measurements and tags.
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- **parse_data_dog_tags** boolean: Enable parsing of tags in DataDog's dogstatsd format (http://docs.datadoghq.com/guides/dogstatsd/)
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### Statsd bucket -> InfluxDB line-protocol Templates
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The plugin supports specifying templates for transforming statsd buckets into
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InfluxDB measurement names and tags. The templates have a _measurement_ keyword,
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which can be used to specify parts of the bucket that are to be used in the
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measurement name. Other words in the template are used as tag names. For example,
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the following template:
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```
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templates = [
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"measurement.measurement.region"
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]
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```
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would result in the following transformation:
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```
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cpu.load.us-west:100|g
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=> cpu_load,region=us-west 100
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```
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Users can also filter the template to use based on the name of the bucket,
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using glob matching, like so:
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```
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templates = [
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"cpu.* measurement.measurement.region",
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"mem.* measurement.measurement.host"
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]
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```
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which would result in the following transformation:
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```
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cpu.load.us-west:100|g
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=> cpu_load,region=us-west 100
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mem.cached.localhost:256|g
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=> mem_cached,host=localhost 256
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```
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There are many more options available,
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[More details can be found here](https://github.com/influxdata/telegraf/blob/master/docs/DATA_FORMATS_INPUT.md#graphite)
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