757 lines
24 KiB
Markdown
757 lines
24 KiB
Markdown
# Telegraf Input Data Formats
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Telegraf is able to parse the following input data formats into metrics:
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1. [InfluxDB Line Protocol](https://github.com/influxdata/telegraf/blob/master/docs/DATA_FORMATS_INPUT.md#influx)
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1. [JSON](https://github.com/influxdata/telegraf/blob/master/docs/DATA_FORMATS_INPUT.md#json)
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1. [Graphite](https://github.com/influxdata/telegraf/blob/master/docs/DATA_FORMATS_INPUT.md#graphite)
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1. [Value](https://github.com/influxdata/telegraf/blob/master/docs/DATA_FORMATS_INPUT.md#value), ie: 45 or "booyah"
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1. [Nagios](https://github.com/influxdata/telegraf/blob/master/docs/DATA_FORMATS_INPUT.md#nagios) (exec input only)
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1. [Collectd](https://github.com/influxdata/telegraf/blob/master/docs/DATA_FORMATS_INPUT.md#collectd)
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1. [Dropwizard](https://github.com/influxdata/telegraf/blob/master/docs/DATA_FORMATS_INPUT.md#dropwizard)
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1. [Grok](https://github.com/influxdata/telegraf/blob/master/docs/DATA_FORMATS_INPUT.md#grok)
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Telegraf metrics, like InfluxDB
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[points](https://docs.influxdata.com/influxdb/v0.10/write_protocols/line/),
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are a combination of four basic parts:
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1. Measurement Name
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1. Tags
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1. Fields
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1. Timestamp
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These four parts are easily defined when using InfluxDB line-protocol as a
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data format. But there are other data formats that users may want to use which
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require more advanced configuration to create usable Telegraf metrics.
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Plugins such as `exec` and `kafka_consumer` parse textual data. Up until now,
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these plugins were statically configured to parse just a single
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data format. `exec` mostly only supported parsing JSON, and `kafka_consumer` only
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supported data in InfluxDB line-protocol.
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But now we are normalizing the parsing of various data formats across all
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plugins that can support it. You will be able to identify a plugin that supports
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different data formats by the presence of a `data_format` config option, for
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example, in the exec plugin:
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```toml
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[[inputs.exec]]
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## Commands array
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commands = ["/tmp/test.sh", "/usr/bin/mycollector --foo=bar"]
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## measurement name suffix (for separating different commands)
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name_suffix = "_mycollector"
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## Data format to consume.
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## Each data format has its own unique set of configuration options, read
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## more about them here:
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## https://github.com/influxdata/telegraf/blob/master/docs/DATA_FORMATS_INPUT.md
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data_format = "json"
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## Additional configuration options go here
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```
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Each data_format has an additional set of configuration options available, which
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I'll go over below.
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# Influx:
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There are no additional configuration options for InfluxDB line-protocol. The
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metrics are parsed directly into Telegraf metrics.
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#### Influx Configuration:
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```toml
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[[inputs.exec]]
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## Commands array
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commands = ["/tmp/test.sh", "/usr/bin/mycollector --foo=bar"]
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## measurement name suffix (for separating different commands)
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name_suffix = "_mycollector"
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## Data format to consume.
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## Each data format has its own unique set of configuration options, read
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## more about them here:
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## https://github.com/influxdata/telegraf/blob/master/docs/DATA_FORMATS_INPUT.md
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data_format = "influx"
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```
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# JSON:
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The JSON data format flattens JSON into metric _fields_.
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NOTE: Only numerical values are converted to fields, and they are converted
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into a float. strings are ignored unless specified as a tag_key (see below).
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So for example, this JSON:
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```json
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{
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"a": 5,
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"b": {
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"c": 6
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},
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"ignored": "I'm a string"
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}
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```
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Would get translated into _fields_ of a measurement:
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```
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myjsonmetric a=5,b_c=6
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```
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The _measurement_ _name_ is usually the name of the plugin,
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but can be overridden using the `name_override` config option.
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#### JSON Configuration:
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The JSON data format supports specifying "tag keys". If specified, keys
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will be searched for in the root-level of the JSON blob. If the key(s) exist,
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they will be applied as tags to the Telegraf metrics.
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For example, if you had this configuration:
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```toml
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[[inputs.exec]]
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## Commands array
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commands = ["/tmp/test.sh", "/usr/bin/mycollector --foo=bar"]
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## measurement name suffix (for separating different commands)
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name_suffix = "_mycollector"
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## Data format to consume.
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## Each data format has its own unique set of configuration options, read
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## more about them here:
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## https://github.com/influxdata/telegraf/blob/master/docs/DATA_FORMATS_INPUT.md
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data_format = "json"
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## List of tag names to extract from top-level of JSON server response
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tag_keys = [
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"my_tag_1",
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"my_tag_2"
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]
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```
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with this JSON output from a command:
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```json
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{
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"a": 5,
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"b": {
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"c": 6
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},
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"my_tag_1": "foo"
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}
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```
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Your Telegraf metrics would get tagged with "my_tag_1"
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```
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exec_mycollector,my_tag_1=foo a=5,b_c=6
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```
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If the JSON data is an array, then each element of the array is parsed with the configured settings.
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Each resulting metric will be output with the same timestamp.
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For example, if the following configuration:
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```toml
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[[inputs.exec]]
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## Commands array
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commands = ["/usr/bin/mycollector --foo=bar"]
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## measurement name suffix (for separating different commands)
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name_suffix = "_mycollector"
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## Data format to consume.
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## Each data format has its own unique set of configuration options, read
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## more about them here:
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## https://github.com/influxdata/telegraf/blob/master/docs/DATA_FORMATS_INPUT.md
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data_format = "json"
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## List of tag names to extract from top-level of JSON server response
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tag_keys = [
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"my_tag_1",
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"my_tag_2"
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]
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```
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with this JSON output from a command:
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```json
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[
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{
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"a": 5,
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"b": {
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"c": 6
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},
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"my_tag_1": "foo",
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"my_tag_2": "baz"
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},
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{
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"a": 7,
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"b": {
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"c": 8
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},
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"my_tag_1": "bar",
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"my_tag_2": "baz"
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}
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]
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```
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Your Telegraf metrics would get tagged with "my_tag_1" and "my_tag_2"
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```
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exec_mycollector,my_tag_1=foo,my_tag_2=baz a=5,b_c=6
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exec_mycollector,my_tag_1=bar,my_tag_2=baz a=7,b_c=8
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```
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# Value:
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The "value" data format translates single values into Telegraf metrics. This
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is done by assigning a measurement name and setting a single field ("value")
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as the parsed metric.
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#### Value Configuration:
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You **must** tell Telegraf what type of metric to collect by using the
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`data_type` configuration option. Available options are:
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1. integer
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2. float or long
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3. string
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4. boolean
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**Note:** It is also recommended that you set `name_override` to a measurement
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name that makes sense for your metric, otherwise it will just be set to the
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name of the plugin.
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```toml
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[[inputs.exec]]
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## Commands array
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commands = ["cat /proc/sys/kernel/random/entropy_avail"]
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## override the default metric name of "exec"
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name_override = "entropy_available"
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## Data format to consume.
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## Each data format has its own unique set of configuration options, read
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## more about them here:
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## https://github.com/influxdata/telegraf/blob/master/docs/DATA_FORMATS_INPUT.md
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data_format = "value"
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data_type = "integer" # required
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```
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# Graphite:
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The Graphite data format translates graphite _dot_ buckets directly into
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telegraf measurement names, with a single value field, and without any tags.
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By default, the separator is left as ".", but this can be changed using the
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"separator" argument. For more advanced options,
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Telegraf supports specifying "templates" to translate
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graphite buckets into Telegraf metrics.
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Templates are of the form:
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```
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"host.mytag.mytag.measurement.measurement.field*"
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```
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Where the following keywords exist:
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1. `measurement`: specifies that this section of the graphite bucket corresponds
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to the measurement name. This can be specified multiple times.
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2. `field`: specifies that this section of the graphite bucket corresponds
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to the field name. This can be specified multiple times.
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3. `measurement*`: specifies that all remaining elements of the graphite bucket
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correspond to the measurement name.
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4. `field*`: specifies that all remaining elements of the graphite bucket
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correspond to the field name.
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Any part of the template that is not a keyword is treated as a tag key. This
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can also be specified multiple times.
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NOTE: `field*` cannot be used in conjunction with `measurement*`!
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#### Measurement & Tag Templates:
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The most basic template is to specify a single transformation to apply to all
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incoming metrics. So the following template:
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```toml
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templates = [
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"region.region.measurement*"
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]
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```
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would result in the following Graphite -> Telegraf transformation.
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```
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us.west.cpu.load 100
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=> cpu.load,region=us.west value=100
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```
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Multiple templates can also be specified, but these should be differentiated
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using _filters_ (see below for more details)
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```toml
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templates = [
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"*.*.* region.region.measurement", # <- all 3-part measurements will match this one.
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"*.*.*.* region.region.host.measurement", # <- all 4-part measurements will match this one.
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]
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```
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#### Field Templates:
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The field keyword tells Telegraf to give the metric that field name.
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So the following template:
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```toml
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separator = "_"
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templates = [
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"measurement.measurement.field.field.region"
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]
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```
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would result in the following Graphite -> Telegraf transformation.
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```
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cpu.usage.idle.percent.eu-east 100
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=> cpu_usage,region=eu-east idle_percent=100
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```
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The field key can also be derived from all remaining elements of the graphite
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bucket by specifying `field*`:
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```toml
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separator = "_"
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templates = [
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"measurement.measurement.region.field*"
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]
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```
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which would result in the following Graphite -> Telegraf transformation.
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```
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cpu.usage.eu-east.idle.percentage 100
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=> cpu_usage,region=eu-east idle_percentage=100
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```
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#### Filter Templates:
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Users can also filter the template(s) to use based on the name of the bucket,
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using glob matching, like so:
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```toml
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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.eu-east 100
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=> cpu_load,region=eu-east value=100
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mem.cached.localhost 256
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=> mem_cached,host=localhost value=256
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```
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#### Adding Tags:
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Additional tags can be added to a metric that don't exist on the received metric.
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You can add additional tags by specifying them after the pattern.
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Tags have the same format as the line protocol.
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Multiple tags are separated by commas.
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```toml
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templates = [
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"measurement.measurement.field.region datacenter=1a"
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]
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```
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would result in the following Graphite -> Telegraf transformation.
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```
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cpu.usage.idle.eu-east 100
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=> cpu_usage,region=eu-east,datacenter=1a idle=100
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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/influxdb/tree/master/services/graphite#templates)
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#### Graphite Configuration:
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```toml
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[[inputs.exec]]
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## Commands array
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commands = ["/tmp/test.sh", "/usr/bin/mycollector --foo=bar"]
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## measurement name suffix (for separating different commands)
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name_suffix = "_mycollector"
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## Data format to consume.
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## Each data format has its own unique set of configuration options, read
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## more about them here:
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## https://github.com/influxdata/telegraf/blob/master/docs/DATA_FORMATS_INPUT.md
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data_format = "graphite"
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## This string will be used to join the matched values.
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separator = "_"
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## Each template line requires a template pattern. It can have an optional
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## filter before the template and separated by spaces. It can also have optional extra
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## tags following the template. Multiple tags should be separated by commas and no spaces
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## similar to the line protocol format. There can be only one default template.
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## Templates support below format:
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## 1. filter + template
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## 2. filter + template + extra tag(s)
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## 3. filter + template with field key
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## 4. default template
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templates = [
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"*.app env.service.resource.measurement",
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"stats.* .host.measurement* region=eu-east,agent=sensu",
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"stats2.* .host.measurement.field",
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"measurement*"
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]
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```
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# Nagios:
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There are no additional configuration options for Nagios line-protocol. The
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metrics are parsed directly into Telegraf metrics.
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Note: Nagios Input Data Formats is only supported in `exec` input plugin.
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#### Nagios Configuration:
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```toml
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[[inputs.exec]]
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## Commands array
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commands = ["/usr/lib/nagios/plugins/check_load -w 5,6,7 -c 7,8,9"]
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## measurement name suffix (for separating different commands)
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name_suffix = "_mycollector"
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## Data format to consume.
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## Each data format has its own unique set of configuration options, read
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## more about them here:
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## https://github.com/influxdata/telegraf/blob/master/docs/DATA_FORMATS_INPUT.md
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data_format = "nagios"
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```
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# Collectd:
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The collectd format parses the collectd binary network protocol. Tags are
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created for host, instance, type, and type instance. All collectd values are
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added as float64 fields.
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For more information about the binary network protocol see
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[here](https://collectd.org/wiki/index.php/Binary_protocol).
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You can control the cryptographic settings with parser options. Create an
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authentication file and set `collectd_auth_file` to the path of the file, then
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set the desired security level in `collectd_security_level`.
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Additional information including client setup can be found
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[here](https://collectd.org/wiki/index.php/Networking_introduction#Cryptographic_setup).
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You can also change the path to the typesdb or add additional typesdb using
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`collectd_typesdb`.
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#### Collectd Configuration:
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```toml
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[[inputs.socket_listener]]
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service_address = "udp://127.0.0.1:25826"
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name_prefix = "collectd_"
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## Data format to consume.
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## Each data format has its own unique set of configuration options, read
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## more about them here:
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## https://github.com/influxdata/telegraf/blob/master/docs/DATA_FORMATS_INPUT.md
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data_format = "collectd"
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## Authentication file for cryptographic security levels
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collectd_auth_file = "/etc/collectd/auth_file"
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## One of none (default), sign, or encrypt
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collectd_security_level = "encrypt"
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## Path of to TypesDB specifications
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collectd_typesdb = ["/usr/share/collectd/types.db"]
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```
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# Dropwizard:
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The dropwizard format can parse the JSON representation of a single dropwizard metric registry. By default, tags are parsed from metric names as if they were actual influxdb line protocol keys (`measurement<,tag_set>`) which can be overriden by defining custom [measurement & tag templates](./DATA_FORMATS_INPUT.md#measurement--tag-templates). All field value types are supported, `string`, `number` and `boolean`.
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A typical JSON of a dropwizard metric registry:
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```json
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{
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"version": "3.0.0",
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"counters" : {
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"measurement,tag1=green" : {
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"count" : 1
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}
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},
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"meters" : {
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"measurement" : {
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"count" : 1,
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"m15_rate" : 1.0,
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"m1_rate" : 1.0,
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"m5_rate" : 1.0,
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"mean_rate" : 1.0,
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"units" : "events/second"
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}
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},
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"gauges" : {
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"measurement" : {
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"value" : 1
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}
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},
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"histograms" : {
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"measurement" : {
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"count" : 1,
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"max" : 1.0,
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"mean" : 1.0,
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"min" : 1.0,
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"p50" : 1.0,
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"p75" : 1.0,
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"p95" : 1.0,
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"p98" : 1.0,
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"p99" : 1.0,
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"p999" : 1.0,
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"stddev" : 1.0
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}
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},
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"timers" : {
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"measurement" : {
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"count" : 1,
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"max" : 1.0,
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"mean" : 1.0,
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"min" : 1.0,
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"p50" : 1.0,
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"p75" : 1.0,
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"p95" : 1.0,
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"p98" : 1.0,
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"p99" : 1.0,
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"p999" : 1.0,
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"stddev" : 1.0,
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"m15_rate" : 1.0,
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"m1_rate" : 1.0,
|
|
"m5_rate" : 1.0,
|
|
"mean_rate" : 1.0,
|
|
"duration_units" : "seconds",
|
|
"rate_units" : "calls/second"
|
|
}
|
|
}
|
|
}
|
|
```
|
|
|
|
Would get translated into 4 different measurements:
|
|
|
|
```
|
|
measurement,metric_type=counter,tag1=green count=1
|
|
measurement,metric_type=meter count=1,m15_rate=1.0,m1_rate=1.0,m5_rate=1.0,mean_rate=1.0
|
|
measurement,metric_type=gauge value=1
|
|
measurement,metric_type=histogram count=1,max=1.0,mean=1.0,min=1.0,p50=1.0,p75=1.0,p95=1.0,p98=1.0,p99=1.0,p999=1.0
|
|
measurement,metric_type=timer count=1,max=1.0,mean=1.0,min=1.0,p50=1.0,p75=1.0,p95=1.0,p98=1.0,p99=1.0,p999=1.0,stddev=1.0,m15_rate=1.0,m1_rate=1.0,m5_rate=1.0,mean_rate=1.0
|
|
```
|
|
|
|
You may also parse a dropwizard registry from any JSON document which contains a dropwizard registry in some inner field.
|
|
Eg. to parse the following JSON document:
|
|
|
|
```json
|
|
{
|
|
"time" : "2017-02-22T14:33:03.662+02:00",
|
|
"tags" : {
|
|
"tag1" : "green",
|
|
"tag2" : "yellow"
|
|
},
|
|
"metrics" : {
|
|
"counters" : {
|
|
"measurement" : {
|
|
"count" : 1
|
|
}
|
|
},
|
|
"meters" : {},
|
|
"gauges" : {},
|
|
"histograms" : {},
|
|
"timers" : {}
|
|
}
|
|
}
|
|
```
|
|
and translate it into:
|
|
|
|
```
|
|
measurement,metric_type=counter,tag1=green,tag2=yellow count=1 1487766783662000000
|
|
```
|
|
|
|
you simply need to use the following additional configuration properties:
|
|
|
|
```toml
|
|
dropwizard_metric_registry_path = "metrics"
|
|
dropwizard_time_path = "time"
|
|
dropwizard_time_format = "2006-01-02T15:04:05Z07:00"
|
|
dropwizard_tags_path = "tags"
|
|
## tag paths per tag are supported too, eg.
|
|
#[inputs.yourinput.dropwizard_tag_paths]
|
|
# tag1 = "tags.tag1"
|
|
# tag2 = "tags.tag2"
|
|
```
|
|
|
|
|
|
For more information about the dropwizard json format see
|
|
[here](http://metrics.dropwizard.io/3.1.0/manual/json/).
|
|
|
|
#### Dropwizard Configuration:
|
|
|
|
```toml
|
|
[[inputs.exec]]
|
|
## Commands array
|
|
commands = ["curl http://localhost:8080/sys/metrics"]
|
|
timeout = "5s"
|
|
|
|
## Data format to consume.
|
|
## Each data format has its own unique set of configuration options, read
|
|
## more about them here:
|
|
## https://github.com/influxdata/telegraf/blob/master/docs/DATA_FORMATS_INPUT.md
|
|
data_format = "dropwizard"
|
|
|
|
## Used by the templating engine to join matched values when cardinality is > 1
|
|
separator = "_"
|
|
|
|
## Each template line requires a template pattern. It can have an optional
|
|
## filter before the template and separated by spaces. It can also have optional extra
|
|
## tags following the template. Multiple tags should be separated by commas and no spaces
|
|
## similar to the line protocol format. There can be only one default template.
|
|
## Templates support below format:
|
|
## 1. filter + template
|
|
## 2. filter + template + extra tag(s)
|
|
## 3. filter + template with field key
|
|
## 4. default template
|
|
## By providing an empty template array, templating is disabled and measurements are parsed as influxdb line protocol keys (measurement<,tag_set>)
|
|
templates = []
|
|
|
|
## You may use an appropriate [gjson path](https://github.com/tidwall/gjson#path-syntax)
|
|
## to locate the metric registry within the JSON document
|
|
# dropwizard_metric_registry_path = "metrics"
|
|
|
|
## You may use an appropriate [gjson path](https://github.com/tidwall/gjson#path-syntax)
|
|
## to locate the default time of the measurements within the JSON document
|
|
# dropwizard_time_path = "time"
|
|
# dropwizard_time_format = "2006-01-02T15:04:05Z07:00"
|
|
|
|
## You may use an appropriate [gjson path](https://github.com/tidwall/gjson#path-syntax)
|
|
## to locate the tags map within the JSON document
|
|
# dropwizard_tags_path = "tags"
|
|
|
|
## You may even use tag paths per tag
|
|
# [inputs.exec.dropwizard_tag_paths]
|
|
# tag1 = "tags.tag1"
|
|
# tag2 = "tags.tag2"
|
|
```
|
|
|
|
#### Grok
|
|
Parse logstash-style "grok" patterns. Patterns can be added to patterns, or custom patterns read from custom_pattern_files.
|
|
|
|
# View logstash grok pattern docs here:
|
|
# https://www.elastic.co/guide/en/logstash/current/plugins-filters-grok.html
|
|
# All default logstash patterns are supported, these can be viewed here:
|
|
# https://github.com/logstash-plugins/logstash-patterns-core/blob/master/patterns/grok-patterns
|
|
|
|
# Available modifiers:
|
|
# string (default if nothing is specified)
|
|
# int
|
|
# float
|
|
# duration (ie, 5.23ms gets converted to int nanoseconds)
|
|
# tag (converts the field into a tag)
|
|
# drop (drops the field completely)
|
|
# Timestamp modifiers:
|
|
# ts-ansic ("Mon Jan _2 15:04:05 2006")
|
|
# ts-unix ("Mon Jan _2 15:04:05 MST 2006")
|
|
# ts-ruby ("Mon Jan 02 15:04:05 -0700 2006")
|
|
# ts-rfc822 ("02 Jan 06 15:04 MST")
|
|
# ts-rfc822z ("02 Jan 06 15:04 -0700")
|
|
# ts-rfc850 ("Monday, 02-Jan-06 15:04:05 MST")
|
|
# ts-rfc1123 ("Mon, 02 Jan 2006 15:04:05 MST")
|
|
# ts-rfc1123z ("Mon, 02 Jan 2006 15:04:05 -0700")
|
|
# ts-rfc3339 ("2006-01-02T15:04:05Z07:00")
|
|
# ts-rfc3339nano ("2006-01-02T15:04:05.999999999Z07:00")
|
|
# ts-httpd ("02/Jan/2006:15:04:05 -0700")
|
|
# ts-epoch (seconds since unix epoch)
|
|
# ts-epochnano (nanoseconds since unix epoch)
|
|
# ts-"CUSTOM"
|
|
# CUSTOM time layouts must be within quotes and be the representation of the
|
|
# "reference time", which is Mon Jan 2 15:04:05 -0700 MST 2006
|
|
# See https://golang.org/pkg/time/#Parse for more details.
|
|
|
|
# Example log file pattern, example log looks like this:
|
|
# [04/Jun/2016:12:41:45 +0100] 1.25 200 192.168.1.1 5.432µs
|
|
# Breakdown of the DURATION pattern below:
|
|
# NUMBER is a builtin logstash grok pattern matching float & int numbers.
|
|
# [nuµm]? is a regex specifying 0 or 1 of the characters within brackets.
|
|
# s is also regex, this pattern must end in "s".
|
|
# so DURATION will match something like '5.324ms' or '6.1µs' or '10s'
|
|
DURATION %{NUMBER}[nuµm]?s
|
|
RESPONSE_CODE %{NUMBER:response_code:tag}
|
|
RESPONSE_TIME %{DURATION:response_time_ns:duration}
|
|
EXAMPLE_LOG \[%{HTTPDATE:ts:ts-httpd}\] %{NUMBER:myfloat:float} %{RESPONSE_CODE} %{IPORHOST:clientip} %{RESPONSE_TIME}
|
|
|
|
# Wider-ranging username matching vs. logstash built-in %{USER}
|
|
NGUSERNAME [a-zA-Z0-9\.\@\-\+_%]+
|
|
NGUSER %{NGUSERNAME}
|
|
# Wider-ranging client IP matching
|
|
CLIENT (?:%{IPORHOST}|%{HOSTPORT}|::1)
|
|
|
|
##
|
|
## COMMON LOG PATTERNS
|
|
##
|
|
|
|
# apache & nginx logs, this is also known as the "common log format"
|
|
# see https://en.wikipedia.org/wiki/Common_Log_Format
|
|
COMMON_LOG_FORMAT %{CLIENT:client_ip} %{NOTSPACE:ident} %{NOTSPACE:auth} \[%{HTTPDATE:ts:ts-httpd}\] "(?:%{WORD:verb:tag} %{NOTSPACE:request}(?: HTTP/%{NUMBER:http_version:float})?|%{DATA})" %{NUMBER:resp_code:tag} (?:%{NUMBER:resp_bytes:int}|-)
|
|
|
|
# Combined log format is the same as the common log format but with the addition
|
|
# of two quoted strings at the end for "referrer" and "agent"
|
|
# See Examples at http://httpd.apache.org/docs/current/mod/mod_log_config.html
|
|
COMBINED_LOG_FORMAT %{COMMON_LOG_FORMAT} %{QS:referrer} %{QS:agent}
|
|
|
|
# HTTPD log formats
|
|
HTTPD20_ERRORLOG \[%{HTTPDERROR_DATE:timestamp}\] \[%{LOGLEVEL:loglevel:tag}\] (?:\[client %{IPORHOST:clientip}\] ){0,1}%{GREEDYDATA:errormsg}
|
|
HTTPD24_ERRORLOG \[%{HTTPDERROR_DATE:timestamp}\] \[%{WORD:module}:%{LOGLEVEL:loglevel:tag}\] \[pid %{POSINT:pid:int}:tid %{NUMBER:tid:int}\]( \(%{POSINT:proxy_errorcode:int}\)%{DATA:proxy_errormessage}:)?( \[client %{IPORHOST:client}:%{POSINT:clientport}\])? %{DATA:errorcode}: %{GREEDYDATA:message}
|
|
HTTPD_ERRORLOG %{HTTPD20_ERRORLOG}|%{HTTPD24_ERRORLOG}
|
|
|
|
#### Grok Configuration:
|
|
```toml
|
|
[[inputs.reader]]
|
|
## This is a list of patterns to check the given log file(s) for.
|
|
## Note that adding patterns here increases processing time. The most
|
|
## efficient configuration is to have one pattern per logparser.
|
|
## Other common built-in patterns are:
|
|
## %{COMMON_LOG_FORMAT} (plain apache & nginx access logs)
|
|
## %{COMBINED_LOG_FORMAT} (access logs + referrer & agent)
|
|
grok_patterns = ["%{COMBINED_LOG_FORMAT}"]
|
|
|
|
## Name of the outputted measurement name.
|
|
grok_name_override = "apache_access_log"
|
|
|
|
## Full path(s) to custom pattern files.
|
|
grok_custom_pattern_files = []
|
|
|
|
## Custom patterns can also be defined here. Put one pattern per line.
|
|
grok_custom_patterns = '''
|
|
|
|
## Timezone allows you to provide an override for timestamps that
|
|
## don't already include an offset
|
|
## e.g. 04/06/2016 12:41:45 data one two 5.43µs
|
|
##
|
|
## Default: "" which renders UTC
|
|
## Options are as follows:
|
|
## 1. Local -- interpret based on machine localtime
|
|
## 2. "Canada/Eastern" -- Unix TZ values like those found in https://en.wikipedia.org/wiki/List_of_tz_database_time_zones
|
|
## 3. UTC -- or blank/unspecified, will return timestamp in UTC
|
|
grok_timezone = "Canada/Eastern"
|
|
``` |