Split parser/serializer docs (#4690)
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README.md
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README.md
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# Telegraf [![Circle CI](https://circleci.com/gh/influxdata/telegraf.svg?style=svg)](https://circleci.com/gh/influxdata/telegraf) [![Docker pulls](https://img.shields.io/docker/pulls/library/telegraf.svg)](https://hub.docker.com/_/telegraf/)
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Telegraf is an agent written in Go for collecting, processing, aggregating,
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and writing metrics.
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Telegraf is an agent for collecting, processing, aggregating, and writing metrics.
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Design goals are to have a minimal memory footprint with a plugin system so
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that developers in the community can easily add support for collecting metrics
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. For an example configuration referencet from local or remote services.
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that developers in the community can easily add support for collecting
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metrics.
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Telegraf is plugin-driven and has the concept of 4 distinct plugins:
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Telegraf is plugin-driven and has the concept of 4 distinct plugin types:
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1. [Input Plugins](#input-plugins) collect metrics from the system, services, or 3rd party APIs
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2. [Processor Plugins](#processor-plugins) transform, decorate, and/or filter metrics
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3. [Aggregator Plugins](#aggregator-plugins) create aggregate metrics (e.g. mean, min, max, quantiles, etc.)
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4. [Output Plugins](#output-plugins) write metrics to various destinations
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For more information on Processor and Aggregator plugins please [read this](./docs/AGGREGATORS_AND_PROCESSORS.md).
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New plugins are designed to be easy to contribute,
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we'll eagerly accept pull
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New plugins are designed to be easy to contribute, we'll eagerly accept pull
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requests and will manage the set of plugins that Telegraf supports.
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## Contributing
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@ -26,7 +22,7 @@ There are many ways to contribute:
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- Fix and [report bugs](https://github.com/influxdata/telegraf/issues/new)
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- [Improve documentation](https://github.com/influxdata/telegraf/issues?q=is%3Aopen+label%3Adocumentation)
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- [Review code and feature proposals](https://github.com/influxdata/telegraf/pulls)
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- Answer questions on github and on the [Community Site](https://community.influxdata.com/)
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- Answer questions and discuss here on github and on the [Community Site](https://community.influxdata.com/)
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- [Contribute plugins](CONTRIBUTING.md)
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## Installation:
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@ -42,7 +38,7 @@ Ansible role: https://github.com/rossmcdonald/telegraf
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Telegraf requires golang version 1.9 or newer, the Makefile requires GNU make.
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1. [Install Go](https://golang.org/doc/install) >=1.9
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1. [Install Go](https://golang.org/doc/install) >=1.9 (1.10 recommended)
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2. [Install dep](https://golang.github.io/dep/docs/installation.html) ==v0.5.0
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3. Download Telegraf source:
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```
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@ -86,44 +82,47 @@ These builds are generated from the master branch:
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See usage with:
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```
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./telegraf --help
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telegraf --help
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```
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#### Generate a telegraf config file:
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```
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./telegraf config > telegraf.conf
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telegraf config > telegraf.conf
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```
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#### Generate config with only cpu input & influxdb output plugins defined:
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```
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./telegraf --input-filter cpu --output-filter influxdb config
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telegraf --input-filter cpu --output-filter influxdb config
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```
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#### Run a single telegraf collection, outputing metrics to stdout:
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```
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./telegraf --config telegraf.conf --test
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telegraf --config telegraf.conf --test
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```
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#### Run telegraf with all plugins defined in config file:
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```
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./telegraf --config telegraf.conf
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telegraf --config telegraf.conf
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```
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#### Run telegraf, enabling the cpu & memory input, and influxdb output plugins:
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```
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./telegraf --config telegraf.conf --input-filter cpu:mem --output-filter influxdb
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telegraf --config telegraf.conf --input-filter cpu:mem --output-filter influxdb
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```
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## Documentation
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## Configuration
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[Latest Release Documentation][release docs].
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See the [configuration guide](docs/CONFIGURATION.md) for a rundown of the more advanced
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configuration options.
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For documentation on the latest development code see the [documentation index][devel docs].
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[release docs]: https://docs.influxdata.com/telegraf
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[devel docs]: docs
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## Input Plugins
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File diff suppressed because it is too large
Load Diff
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standard data formats that may be selected from when configuring many output
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plugins.
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1. [InfluxDB Line Protocol](#influx)
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1. [JSON](#json)
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1. [Graphite](#graphite)
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1. [SplunkMetric](../plugins/serializers/splunkmetric/README.md)
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1. [InfluxDB Line Protocol](/plugins/serializers/influx)
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1. [JSON](/plugins/serializers/json)
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1. [Graphite](/plugins/serializers/graphite)
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1. [SplunkMetric](/plugins/serializers/splunkmetric)
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You will be able to identify the plugins with support by the presence of a
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`data_format` config option, for example, in the `file` output plugin:
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```toml
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[[outputs.file]]
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## Files to write to, "stdout" is a specially handled file.
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## https://github.com/influxdata/telegraf/blob/master/docs/DATA_FORMATS_OUTPUT.md
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data_format = "influx"
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```
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## Influx
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The `influx` data format outputs metrics using
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[InfluxDB Line Protocol](https://docs.influxdata.com/influxdb/latest/write_protocols/line_protocol_tutorial/).
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This is the recommended format unless another format is required for
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interoperability.
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### Influx Configuration
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```toml
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[[outputs.file]]
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## Files to write to, "stdout" is a specially handled file.
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files = ["stdout", "/tmp/metrics.out"]
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## Data format to output.
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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_OUTPUT.md
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data_format = "influx"
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## Maximum line length in bytes. Useful only for debugging.
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# influx_max_line_bytes = 0
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## When true, fields will be output in ascending lexical order. Enabling
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## this option will result in decreased performance and is only recommended
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## when you need predictable ordering while debugging.
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# influx_sort_fields = false
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## When true, Telegraf will output unsigned integers as unsigned values,
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## i.e.: `42u`. You will need a version of InfluxDB supporting unsigned
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## integer values. Enabling this option will result in field type errors if
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## existing data has been written.
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# influx_uint_support = false
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```
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## Graphite
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The Graphite data format is translated from Telegraf Metrics using either the
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template pattern or tag support method. You can select between the two
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methods using the [`graphite_tag_support`](#graphite-tag-support) option. When set, the tag support
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method is used, otherwise the [`template` pattern](#template-pattern) is used.
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#### Template Pattern
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The `template` option describes how Telegraf traslates metrics into _dot_
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buckets. The default template is:
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```
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template = "host.tags.measurement.field"
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```
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In the above template, we have four parts:
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1. _host_ is a tag key. This can be any tag key that is in the Telegraf
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metric(s). If the key doesn't exist, it will be ignored. If it does exist, the
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tag value will be filled in.
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1. _tags_ is a special keyword that outputs all remaining tag values, separated
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by dots and in alphabetical order (by tag key). These will be filled after all
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tag keys are filled.
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1. _measurement_ is a special keyword that outputs the measurement name.
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1. _field_ is a special keyword that outputs the field name.
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**Example Conversion**:
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```
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cpu,cpu=cpu-total,dc=us-east-1,host=tars usage_idle=98.09,usage_user=0.89 1455320660004257758
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=>
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tars.cpu-total.us-east-1.cpu.usage_user 0.89 1455320690
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tars.cpu-total.us-east-1.cpu.usage_idle 98.09 1455320690
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```
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Fields with string values will be skipped. Boolean fields will be converted
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to 1 (true) or 0 (false).
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#### Graphite Tag Support
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When the `graphite_tag_support` option is enabled, the template pattern is not
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used. Instead, tags are encoded using
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[Graphite tag support](http://graphite.readthedocs.io/en/latest/tags.html)
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added in Graphite 1.1. The `metric_path` is a combination of the optional
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`prefix` option, measurement name, and field name.
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The tag `name` is reserved by Graphite, any conflicting tags and will be encoded as `_name`.
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**Example Conversion**:
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```
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cpu,cpu=cpu-total,dc=us-east-1,host=tars usage_idle=98.09,usage_user=0.89 1455320660004257758
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=>
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cpu.usage_user;cpu=cpu-total;dc=us-east-1;host=tars 0.89 1455320690
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cpu.usage_idle;cpu=cpu-total;dc=us-east-1;host=tars 98.09 1455320690
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```
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### Graphite Configuration
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```toml
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[[outputs.file]]
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## Files to write to, "stdout" is a specially handled file.
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files = ["stdout", "/tmp/metrics.out"]
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## Data format to output.
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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_OUTPUT.md
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data_format = "graphite"
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## Prefix added to each graphite bucket
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prefix = "telegraf"
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## Graphite template pattern
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template = "host.tags.measurement.field"
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## Support Graphite tags, recommended to enable when using Graphite 1.1 or later.
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# graphite_tag_support = false
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```
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## JSON
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The JSON output data format output for a single metric is in the
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form:
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```json
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{
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"fields": {
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"field_1": 30,
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"field_2": 4,
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"field_N": 59,
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"n_images": 660
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},
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"name": "docker",
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"tags": {
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"host": "raynor"
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},
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"timestamp": 1458229140
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}
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```
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When an output plugin needs to emit multiple metrics at one time, it may use
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the batch format. The use of batch format is determined by the plugin,
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reference the documentation for the specific plugin.
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```json
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{
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"metrics": [
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{
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"fields": {
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"field_1": 30,
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"field_2": 4,
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"field_N": 59,
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"n_images": 660
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},
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"name": "docker",
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"tags": {
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"host": "raynor"
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},
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"timestamp": 1458229140
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},
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{
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"fields": {
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"field_1": 30,
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"field_2": 4,
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"field_N": 59,
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"n_images": 660
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},
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"name": "docker",
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"tags": {
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"host": "raynor"
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},
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"timestamp": 1458229140
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}
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]
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}
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```
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### JSON Configuration
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```toml
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[[outputs.file]]
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## Files to write to, "stdout" is a specially handled file.
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files = ["stdout", "/tmp/metrics.out"]
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## Data format to output.
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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_OUTPUT.md
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data_format = "json"
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## The resolution to use for the metric timestamp. Must be a duration string
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## such as "1ns", "1us", "1ms", "10ms", "1s". Durations are truncated to
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## the power of 10 less than the specified units.
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json_timestamp_units = "1s"
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```
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# Metrics
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Telegraf metrics are the internal representation used to model data during
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processing. Metrics are closely based on InfluxDB's data model and contain
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four main components:
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- **Measurement Name**: Description and namespace for the metric.
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- **Tags**: Key/Value string pairs and usually used to identify the
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metric.
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- **Fields**: Key/Value pairs that are typed and usually contain the
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metric data.
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- **Timestamp**: Date and time associated with the fields.
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This metric type exists only in memory and must be converted to a concrete
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representation in order to be transmitted or viewed. To acheive this we
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provide several [output data formats][] sometimes referred to as
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*serializers*. Our default serializer converts to [InfluxDB Line
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Protocol][line protocol] which provides a high performance and one-to-one
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direct mapping from Telegraf metrics.
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[output data formats]: /docs/DATA_FORMATS_OUTPUT.md
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[line protocol]: /plugins/serializers/influx
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# Telegraf
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- Concepts
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- [Metrics][metrics]
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- [Input Data Formats][parsers]
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- [Output Data Formats][serializers]
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- [Aggregators & Processors][aggproc]
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- Administration
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- [Configuration][conf]
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- [Profiling][profiling]
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- [Windows Service][winsvc]
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- [FAQ][faq]
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[conf]: /docs/CONFIGURATION.md
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[metrics]: /docs/METRICS.md
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[parsers]: /docs/DATA_FORMATS_INPUT.md
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[serializers]: /docs/DATA_FORMATS_OUTPUT.md
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[aggproc]: /docs/AGGREGATORS_AND_PROCESSORS.md
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[profiling]: /docs/PROFILING.md
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[winsvc]: /docs/WINDOWS_SERVICE.md
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[faq]: /docs/FAQ.md
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# Template Patterns
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Template patterns are a mini language that describes how a dot delimited
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string should be mapped to and from [metrics][].
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A template has 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 can be set:
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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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### Examples
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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.
|
||||
Tags have the same format as the line protocol.
|
||||
Multiple tags are separated by commas.
|
||||
|
||||
```toml
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templates = [
|
||||
"measurement.measurement.field.region datacenter=1a"
|
||||
]
|
||||
```
|
||||
|
||||
would result in the following Graphite -> Telegraf transformation.
|
||||
|
||||
```
|
||||
cpu.usage.idle.eu-east 100
|
||||
=> cpu_usage,region=eu-east,datacenter=1a idle=100
|
||||
```
|
||||
|
||||
[metrics]: /docs/METRICS.md
|
|
@ -45,7 +45,7 @@
|
|||
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
|
||||
## https://github.com/influxdata/telegraf/blob/master/docs/TEMPLATE_PATTERN.md
|
||||
# templates = [
|
||||
# "cpu.* measurement*"
|
||||
# ]
|
||||
|
@ -227,5 +227,5 @@ mem.cached.localhost:256|g
|
|||
=> mem_cached,host=localhost 256
|
||||
```
|
||||
|
||||
There are many more options available,
|
||||
[More details can be found here](https://github.com/influxdata/telegraf/blob/master/docs/DATA_FORMATS_INPUT.md#graphite)
|
||||
Consult the [Template Patterns](/docs/TEMPLATE_PATTERN.md) documentation for
|
||||
additional details.
|
||||
|
|
|
@ -216,7 +216,7 @@ const sampleConfig = `
|
|||
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
|
||||
## https://github.com/influxdata/telegraf/blob/master/docs/TEMPLATE_PATTERN.md
|
||||
# templates = [
|
||||
# "cpu.* measurement*"
|
||||
# ]
|
||||
|
|
|
@ -0,0 +1,46 @@
|
|||
# Example
|
||||
|
||||
This description explains at a high level what the parser does and provides
|
||||
links to where additional information about the format can be found.
|
||||
|
||||
### Configuration
|
||||
|
||||
This section contains the sample configuration for the parser. Since the
|
||||
configuration for a parser is not have a standalone plugin, use the `file` or
|
||||
`exec` input as the base config.
|
||||
|
||||
```toml
|
||||
[[inputs.file]]
|
||||
files = ["example"]
|
||||
|
||||
## 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 = "example"
|
||||
|
||||
## Describe variables using the standard SampleConfig style.
|
||||
## https://github.com/influxdata/telegraf/wiki/SampleConfig
|
||||
example_option = "example_value"
|
||||
```
|
||||
|
||||
#### example_option
|
||||
|
||||
If an option requires a more expansive explanation than can be included inline
|
||||
in the sample configuration, it may be described here.
|
||||
|
||||
### Metrics
|
||||
|
||||
The optional Metrics section contains details about how the parser converts
|
||||
input data into Telegraf metrics.
|
||||
|
||||
### Examples
|
||||
|
||||
The optional Examples section can show an example conversion from the input
|
||||
format using InfluxDB Line Protocol as the reference format.
|
||||
|
||||
For line delimited text formats a diff may be appropriate:
|
||||
```diff
|
||||
- cpu|host=localhost|source=example.org|value=42
|
||||
+ cpu,host=localhost,source=example.org value=42
|
||||
```
|
|
@ -0,0 +1,44 @@
|
|||
# Collectd
|
||||
|
||||
The collectd format parses the collectd binary network protocol. Tags are
|
||||
created for host, instance, type, and type instance. All collectd values are
|
||||
added as float64 fields.
|
||||
|
||||
For more information about the binary network protocol see
|
||||
[here](https://collectd.org/wiki/index.php/Binary_protocol).
|
||||
|
||||
You can control the cryptographic settings with parser options. Create an
|
||||
authentication file and set `collectd_auth_file` to the path of the file, then
|
||||
set the desired security level in `collectd_security_level`.
|
||||
|
||||
Additional information including client setup can be found
|
||||
[here](https://collectd.org/wiki/index.php/Networking_introduction#Cryptographic_setup).
|
||||
|
||||
You can also change the path to the typesdb or add additional typesdb using
|
||||
`collectd_typesdb`.
|
||||
|
||||
### Configuration
|
||||
|
||||
```toml
|
||||
[[inputs.file]]
|
||||
files = ["example"]
|
||||
|
||||
## 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 = "collectd"
|
||||
|
||||
## Authentication file for cryptographic security levels
|
||||
collectd_auth_file = "/etc/collectd/auth_file"
|
||||
## One of none (default), sign, or encrypt
|
||||
collectd_security_level = "encrypt"
|
||||
## Path of to TypesDB specifications
|
||||
collectd_typesdb = ["/usr/share/collectd/types.db"]
|
||||
|
||||
## Multi-value plugins can be handled two ways.
|
||||
## "split" will parse and store the multi-value plugin data into separate measurements
|
||||
## "join" will parse and store the multi-value plugin as a single multi-value measurement.
|
||||
## "split" is the default behavior for backward compatability with previous versions of influxdb.
|
||||
collectd_parse_multivalue = "split"
|
||||
```
|
|
@ -0,0 +1,104 @@
|
|||
# CSV
|
||||
|
||||
The `csv` parser creates metrics from a document containing comma separated
|
||||
values.
|
||||
|
||||
### Configuration
|
||||
|
||||
```toml
|
||||
[[inputs.file]]
|
||||
files = ["example"]
|
||||
|
||||
## 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 = "csv"
|
||||
|
||||
## Indicates how many rows to treat as a header. By default, the parser assumes
|
||||
## there is no header and will parse the first row as data. If set to anything more
|
||||
## than 1, column names will be concatenated with the name listed in the next header row.
|
||||
## If `csv_column_names` is specified, the column names in header will be overridden.
|
||||
csv_header_row_count = 0
|
||||
|
||||
## For assigning custom names to columns
|
||||
## If this is specified, all columns should have a name
|
||||
## Unnamed columns will be ignored by the parser.
|
||||
## If `csv_header_row_count` is set to 0, this config must be used
|
||||
csv_column_names = []
|
||||
|
||||
## Indicates the number of rows to skip before looking for header information.
|
||||
csv_skip_rows = 0
|
||||
|
||||
## Indicates the number of columns to skip before looking for data to parse.
|
||||
## These columns will be skipped in the header as well.
|
||||
csv_skip_columns = 0
|
||||
|
||||
## The seperator between csv fields
|
||||
## By default, the parser assumes a comma (",")
|
||||
csv_delimiter = ","
|
||||
|
||||
## The character reserved for marking a row as a comment row
|
||||
## Commented rows are skipped and not parsed
|
||||
csv_comment = ""
|
||||
|
||||
## If set to true, the parser will remove leading whitespace from fields
|
||||
## By default, this is false
|
||||
csv_trim_space = false
|
||||
|
||||
## Columns listed here will be added as tags. Any other columns
|
||||
## will be added as fields.
|
||||
csv_tag_columns = []
|
||||
|
||||
## The column to extract the name of the metric from
|
||||
csv_measurement_column = ""
|
||||
|
||||
## The column to extract time information for the metric
|
||||
## `csv_timestamp_format` must be specified if this is used
|
||||
csv_timestamp_column = ""
|
||||
|
||||
## The format of time data extracted from `csv_timestamp_column`
|
||||
## this must be specified if `csv_timestamp_column` is specified
|
||||
csv_timestamp_format = ""
|
||||
```
|
||||
#### csv_timestamp_column, csv_timestamp_format
|
||||
|
||||
By default the current time will be used for all created metrics, to set the
|
||||
time using the JSON document you can use the `csv_timestamp_column` and
|
||||
`csv_timestamp_format` options together to set the time to a value in the parsed
|
||||
document.
|
||||
|
||||
The `csv_timestamp_column` option specifies the column name containing the
|
||||
time value and `csv_timestamp_format` must be set to a Go "reference time"
|
||||
which is defined to be the specific time: `Mon Jan 2 15:04:05 MST 2006`.
|
||||
|
||||
Consult the Go [time][time parse] package for details and additional examples
|
||||
on how to set the time format.
|
||||
|
||||
### Metrics
|
||||
|
||||
One metric is created for each row with the columns added as fields. The type
|
||||
of the field is automatically determined based on the contents of the value.
|
||||
|
||||
### Examples
|
||||
|
||||
Config:
|
||||
```
|
||||
[[inputs.file]]
|
||||
files = ["example"]
|
||||
data_format = "csv"
|
||||
csv_header_row_count = 1
|
||||
csv_timestamp_column = "time"
|
||||
csv_timestamp_format = "2006-01-02T15:04:05Z07:00"
|
||||
```
|
||||
|
||||
Input:
|
||||
```
|
||||
measurement,cpu,time_user,time_system,time_idle,time
|
||||
cpu,cpu0,42,42,42,2018-09-13T13:03:28Z
|
||||
```
|
||||
|
||||
Output:
|
||||
```
|
||||
cpu cpu=cpu0,time_user=42,time_system=42,time_idle=42 1536869008000000000
|
||||
```
|
|
@ -0,0 +1,171 @@
|
|||
# Dropwizard
|
||||
|
||||
The `dropwizard` data format can parse the [JSON Dropwizard][dropwizard] 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 a custom [template pattern][templates]. All field value types are supported, `string`, `number` and `boolean`.
|
||||
|
||||
[templates]: /docs/TEMPLATE_PATTERN.md
|
||||
[dropwizard]: http://metrics.dropwizard.io/3.1.0/manual/json/
|
||||
|
||||
### Configuration
|
||||
|
||||
```toml
|
||||
[[inputs.file]]
|
||||
files = ["example"]
|
||||
|
||||
## 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"
|
||||
```
|
||||
|
||||
|
||||
### Examples
|
||||
|
||||
A typical JSON of a dropwizard metric registry:
|
||||
|
||||
```json
|
||||
{
|
||||
"version": "3.0.0",
|
||||
"counters" : {
|
||||
"measurement,tag1=green" : {
|
||||
"count" : 1
|
||||
}
|
||||
},
|
||||
"meters" : {
|
||||
"measurement" : {
|
||||
"count" : 1,
|
||||
"m15_rate" : 1.0,
|
||||
"m1_rate" : 1.0,
|
||||
"m5_rate" : 1.0,
|
||||
"mean_rate" : 1.0,
|
||||
"units" : "events/second"
|
||||
}
|
||||
},
|
||||
"gauges" : {
|
||||
"measurement" : {
|
||||
"value" : 1
|
||||
}
|
||||
},
|
||||
"histograms" : {
|
||||
"measurement" : {
|
||||
"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
|
||||
}
|
||||
},
|
||||
"timers" : {
|
||||
"measurement" : {
|
||||
"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,
|
||||
"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"
|
||||
```
|
|
@ -0,0 +1,48 @@
|
|||
# Graphite
|
||||
|
||||
The Graphite data format translates graphite *dot* buckets directly into
|
||||
telegraf measurement names, with a single value field, and without any tags.
|
||||
By default, the separator is left as `.`, but this can be changed using the
|
||||
`separator` argument. For more advanced options, Telegraf supports specifying
|
||||
[templates](#templates) to translate graphite buckets into Telegraf metrics.
|
||||
|
||||
### Configuration
|
||||
|
||||
```toml
|
||||
[[inputs.exec]]
|
||||
## Commands array
|
||||
commands = ["/tmp/test.sh", "/usr/bin/mycollector --foo=bar"]
|
||||
|
||||
## measurement name suffix (for separating different commands)
|
||||
name_suffix = "_mycollector"
|
||||
|
||||
## 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 = "graphite"
|
||||
|
||||
## This string will be used to join the matched values.
|
||||
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
|
||||
templates = [
|
||||
"*.app env.service.resource.measurement",
|
||||
"stats.* .host.measurement* region=eu-east,agent=sensu",
|
||||
"stats2.* .host.measurement.field",
|
||||
"measurement*"
|
||||
]
|
||||
```
|
||||
|
||||
#### templates
|
||||
|
||||
Consult the [Template Patterns](/docs/TEMPLATE_PATTERN.md) documentation for
|
||||
details.
|
|
@ -0,0 +1,222 @@
|
|||
# Grok
|
||||
|
||||
The grok data format parses line delimited data using a regular expression like
|
||||
language.
|
||||
|
||||
The best way to get acquainted with grok patterns is to read the logstash docs,
|
||||
which are available here:
|
||||
https://www.elastic.co/guide/en/logstash/current/plugins-filters-grok.html
|
||||
|
||||
The grok parser uses a slightly modified version of logstash "grok"
|
||||
patterns, with the format:
|
||||
|
||||
```
|
||||
%{<capture_syntax>[:<semantic_name>][:<modifier>]}
|
||||
```
|
||||
|
||||
The `capture_syntax` defines the grok pattern that's used to parse the input
|
||||
line and the `semantic_name` is used to name the field or tag. The extension
|
||||
`modifier` controls the data type that the parsed item is converted to or
|
||||
other special handling.
|
||||
|
||||
By default all named captures are converted into string fields.
|
||||
Timestamp modifiers can be used to convert captures to the timestamp of the
|
||||
parsed metric. If no timestamp is parsed the metric will be created using the
|
||||
current time.
|
||||
|
||||
You must capture at least one field per line.
|
||||
|
||||
- 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)
|
||||
- measurement (use the matched text as the measurement name)
|
||||
- Timestamp modifiers:
|
||||
- ts (This will auto-learn the timestamp format)
|
||||
- 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, may contain decimal)
|
||||
- ts-epochnano (nanoseconds since unix epoch)
|
||||
- ts-syslog ("Jan 02 15:04:05", parsed time is set to the current year)
|
||||
- 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`.
|
||||
To match a comma decimal point you can use a period. For example `%{TIMESTAMP:timestamp:ts-"2006-01-02 15:04:05.000"}` can be used to match `"2018-01-02 15:04:05,000"`
|
||||
To match a comma decimal point you can use a period in the pattern string.
|
||||
See https://golang.org/pkg/time/#Parse for more details.
|
||||
|
||||
Telegraf has many of its own [built-in patterns](./grok/patterns/influx-patterns),
|
||||
as well as support for most of
|
||||
[logstash's builtin patterns](https://github.com/logstash-plugins/logstash-patterns-core/blob/master/patterns/grok-patterns).
|
||||
_Golang regular expressions do not support lookahead or lookbehind.
|
||||
logstash patterns that depend on these are not supported._
|
||||
|
||||
If you need help building patterns to match your logs,
|
||||
you will find the https://grokdebug.herokuapp.com application quite useful!
|
||||
|
||||
### Configuration
|
||||
```toml
|
||||
[[inputs.file]]
|
||||
## Files to parse each interval.
|
||||
## These accept standard unix glob matching rules, but with the addition of
|
||||
## ** as a "super asterisk". ie:
|
||||
## /var/log/**.log -> recursively find all .log files in /var/log
|
||||
## /var/log/*/*.log -> find all .log files with a parent dir in /var/log
|
||||
## /var/log/apache.log -> only tail the apache log file
|
||||
files = ["/var/log/apache/access.log"]
|
||||
|
||||
## The dataformat to be read from files
|
||||
## 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 = "grok"
|
||||
|
||||
## 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.
|
||||
## 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}"]
|
||||
|
||||
## 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"
|
||||
```
|
||||
|
||||
#### Timestamp Examples
|
||||
|
||||
This example input and config parses a file using a custom timestamp conversion:
|
||||
|
||||
```
|
||||
2017-02-21 13:10:34 value=42
|
||||
```
|
||||
|
||||
```toml
|
||||
[[inputs.file]]
|
||||
grok_patterns = ['%{TIMESTAMP_ISO8601:timestamp:ts-"2006-01-02 15:04:05"} value=%{NUMBER:value:int}']
|
||||
```
|
||||
|
||||
This example input and config parses a file using a timestamp in unix time:
|
||||
|
||||
```
|
||||
1466004605 value=42
|
||||
1466004605.123456789 value=42
|
||||
```
|
||||
|
||||
```toml
|
||||
[[inputs.file]]
|
||||
grok_patterns = ['%{NUMBER:timestamp:ts-epoch} value=%{NUMBER:value:int}']
|
||||
```
|
||||
|
||||
This example parses a file using a built-in conversion and a custom pattern:
|
||||
|
||||
```
|
||||
Wed Apr 12 13:10:34 PST 2017 value=42
|
||||
```
|
||||
|
||||
```toml
|
||||
[[inputs.file]]
|
||||
grok_patterns = ["%{TS_UNIX:timestamp:ts-unix} value=%{NUMBER:value:int}"]
|
||||
grok_custom_patterns = '''
|
||||
TS_UNIX %{DAY} %{MONTH} %{MONTHDAY} %{HOUR}:%{MINUTE}:%{SECOND} %{TZ} %{YEAR}
|
||||
'''
|
||||
```
|
||||
|
||||
For cases where the timestamp itself is without offset, the `timezone` config var is available
|
||||
to denote an offset. By default (with `timezone` either omit, blank or set to `"UTC"`), the times
|
||||
are processed as if in the UTC timezone. If specified as `timezone = "Local"`, the timestamp
|
||||
will be processed based on the current machine timezone configuration. Lastly, if using a
|
||||
timezone from the list of Unix [timezones](https://en.wikipedia.org/wiki/List_of_tz_database_time_zones),
|
||||
grok will offset the timestamp accordingly.
|
||||
|
||||
#### TOML Escaping
|
||||
|
||||
When saving patterns to the configuration file, keep in mind the different TOML
|
||||
[string](https://github.com/toml-lang/toml#string) types and the escaping
|
||||
rules for each. These escaping rules must be applied in addition to the
|
||||
escaping required by the grok syntax. Using the Multi-line line literal
|
||||
syntax with `'''` may be useful.
|
||||
|
||||
The following config examples will parse this input file:
|
||||
|
||||
```
|
||||
|42|\uD83D\uDC2F|'telegraf'|
|
||||
```
|
||||
|
||||
Since `|` is a special character in the grok language, we must escape it to
|
||||
get a literal `|`. With a basic TOML string, special characters such as
|
||||
backslash must be escaped, requiring us to escape the backslash a second time.
|
||||
|
||||
```toml
|
||||
[[inputs.file]]
|
||||
grok_patterns = ["\\|%{NUMBER:value:int}\\|%{UNICODE_ESCAPE:escape}\\|'%{WORD:name}'\\|"]
|
||||
grok_custom_patterns = "UNICODE_ESCAPE (?:\\\\u[0-9A-F]{4})+"
|
||||
```
|
||||
|
||||
We cannot use a literal TOML string for the pattern, because we cannot match a
|
||||
`'` within it. However, it works well for the custom pattern.
|
||||
```toml
|
||||
[[inputs.file]]
|
||||
grok_patterns = ["\\|%{NUMBER:value:int}\\|%{UNICODE_ESCAPE:escape}\\|'%{WORD:name}'\\|"]
|
||||
grok_custom_patterns = 'UNICODE_ESCAPE (?:\\u[0-9A-F]{4})+'
|
||||
```
|
||||
|
||||
A multi-line literal string allows us to encode the pattern:
|
||||
```toml
|
||||
[[inputs.file]]
|
||||
grok_patterns = ['''
|
||||
\|%{NUMBER:value:int}\|%{UNICODE_ESCAPE:escape}\|'%{WORD:name}'\|
|
||||
''']
|
||||
grok_custom_patterns = 'UNICODE_ESCAPE (?:\\u[0-9A-F]{4})+'
|
||||
```
|
||||
|
||||
#### Tips for creating patterns
|
||||
|
||||
Writing complex patterns can be difficult, here is some advice for writing a
|
||||
new pattern or testing a pattern developed [online](https://grokdebug.herokuapp.com).
|
||||
|
||||
Create a file output that writes to stdout, and disable other outputs while
|
||||
testing. This will allow you to see the captured metrics. Keep in mind that
|
||||
the file output will only print once per `flush_interval`.
|
||||
|
||||
```toml
|
||||
[[outputs.file]]
|
||||
files = ["stdout"]
|
||||
```
|
||||
|
||||
- Start with a file containing only a single line of your input.
|
||||
- Remove all but the first token or piece of the line.
|
||||
- Add the section of your pattern to match this piece to your configuration file.
|
||||
- Verify that the metric is parsed successfully by running Telegraf.
|
||||
- If successful, add the next token, update the pattern and retest.
|
||||
- Continue one token at a time until the entire line is successfully parsed.
|
||||
|
||||
|
|
@ -0,0 +1,20 @@
|
|||
# InfluxDB Line Protocol
|
||||
|
||||
There are no additional configuration options for InfluxDB [line protocol][]. The
|
||||
metrics are parsed directly into Telegraf metrics.
|
||||
|
||||
[line protocol]: https://docs.influxdata.com/influxdb/latest/write_protocols/line/
|
||||
|
||||
### Configuration
|
||||
|
||||
```toml
|
||||
[[inputs.file]]
|
||||
files = ["example"]
|
||||
|
||||
## 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 = "influx"
|
||||
```
|
||||
|
|
@ -0,0 +1,214 @@
|
|||
# JSON
|
||||
|
||||
The JSON data format parses a [JSON][json] object or an array of objects into
|
||||
metric fields.
|
||||
|
||||
**NOTE:** All JSON numbers are converted to float fields. JSON String are
|
||||
ignored unless specified in the `tag_key` or `json_string_fields` options.
|
||||
|
||||
### Configuration
|
||||
|
||||
```toml
|
||||
[[inputs.file]]
|
||||
files = ["example"]
|
||||
|
||||
## 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 = "json"
|
||||
|
||||
## Query is a GJSON path that specifies a specific chunk of JSON to be
|
||||
## parsed, if not specified the whole document will be parsed.
|
||||
##
|
||||
## GJSON query paths are described here:
|
||||
## https://github.com/tidwall/gjson#path-syntax
|
||||
json_query = ""
|
||||
|
||||
## Tag keys is an array of keys that should be added as tags.
|
||||
tag_keys = [
|
||||
"my_tag_1",
|
||||
"my_tag_2"
|
||||
]
|
||||
|
||||
## String fields is an array of keys that should be added as string fields.
|
||||
json_string_fields = []
|
||||
|
||||
## Name key is the key to use as the measurement name.
|
||||
json_name_key = ""
|
||||
|
||||
## Time key is the key containing the time that should be used to create the
|
||||
## metric.
|
||||
json_time_key = ""
|
||||
|
||||
## Time format is the time layout that should be used to interprete the
|
||||
## json_time_key. The time must be `unix`, `unix_ms` or a time in the
|
||||
## "reference time".
|
||||
## ex: json_time_format = "Mon Jan 2 15:04:05 -0700 MST 2006"
|
||||
## json_time_format = "2006-01-02T15:04:05Z07:00"
|
||||
## json_time_format = "unix"
|
||||
## json_time_format = "unix_ms"
|
||||
json_time_format = ""
|
||||
```
|
||||
|
||||
#### json_query
|
||||
|
||||
The `json_query` is a [GJSON][gjson] path that can be used to limit the
|
||||
portion of the overall JSON document that should be parsed. The result of the
|
||||
query should contain a JSON object or an array of objects.
|
||||
|
||||
Consult the GJSON [path syntax][gjson syntax] for details and examples.
|
||||
|
||||
#### json_time_key, json_time_format
|
||||
|
||||
By default the current time will be used for all created metrics, to set the
|
||||
time using the JSON document you can use the `json_time_key` and
|
||||
`json_time_format` options together to set the time to a value in the parsed
|
||||
document.
|
||||
|
||||
The `json_time_key` option specifies the key containing the time value and
|
||||
`json_time_format` must be set to `unix`, `unix_ms`, or the Go "reference
|
||||
time" which is defined to be the specific time: `Mon Jan 2 15:04:05 MST 2006`.
|
||||
|
||||
Consult the Go [time][time parse] package for details and additional examples
|
||||
on how to set the time format.
|
||||
|
||||
### Examples
|
||||
|
||||
#### Basic Parsing
|
||||
Config:
|
||||
```toml
|
||||
[[inputs.file]]
|
||||
files = ["example"]
|
||||
name_override = "myjsonmetric"
|
||||
data_format = "json"
|
||||
```
|
||||
|
||||
Input:
|
||||
```json
|
||||
{
|
||||
"a": 5,
|
||||
"b": {
|
||||
"c": 6
|
||||
},
|
||||
"ignored": "I'm a string"
|
||||
}
|
||||
```
|
||||
|
||||
Output:
|
||||
```
|
||||
myjsonmetric a=5,b_c=6
|
||||
```
|
||||
|
||||
#### Name, Tags, and String Fields
|
||||
|
||||
Config:
|
||||
```toml
|
||||
[[inputs.file]]
|
||||
files = ["example"]
|
||||
name_key = "name"
|
||||
tag_keys = ["my_tag_1"]
|
||||
string_fields = ["my_field"]
|
||||
data_format = "json"
|
||||
```
|
||||
|
||||
Input:
|
||||
```json
|
||||
{
|
||||
"a": 5,
|
||||
"b": {
|
||||
"c": 6,
|
||||
"my_field": "description"
|
||||
},
|
||||
"my_tag_1": "foo",
|
||||
"name": "my_json"
|
||||
}
|
||||
```
|
||||
|
||||
Output:
|
||||
```
|
||||
my_json,my_tag_1=foo a=5,b_c=6,my_field="description"
|
||||
```
|
||||
|
||||
#### Arrays
|
||||
|
||||
If the JSON data is an array, then each object within the array is parsed with
|
||||
the configured settings.
|
||||
|
||||
Config:
|
||||
```toml
|
||||
[[inputs.file]]
|
||||
files = ["example"]
|
||||
data_format = "json"
|
||||
json_time_key = "b_time"
|
||||
json_time_format = "02 Jan 06 15:04 MST"
|
||||
```
|
||||
|
||||
Input:
|
||||
```json
|
||||
[
|
||||
{
|
||||
"a": 5,
|
||||
"b": {
|
||||
"c": 6,
|
||||
"time":"04 Jan 06 15:04 MST"
|
||||
},
|
||||
},
|
||||
{
|
||||
"a": 7,
|
||||
"b": {
|
||||
"c": 8,
|
||||
"time":"11 Jan 07 15:04 MST"
|
||||
},
|
||||
}
|
||||
]
|
||||
```
|
||||
|
||||
Output:
|
||||
```
|
||||
file a=5,b_c=6 1136387040000000000
|
||||
file a=7,b_c=8 1168527840000000000
|
||||
```
|
||||
|
||||
#### Query
|
||||
|
||||
The `json_query` option can be used to parse a subset of the document.
|
||||
|
||||
Config:
|
||||
```toml
|
||||
[[inputs.file]]
|
||||
files = ["example"]
|
||||
data_format = "json"
|
||||
tag_keys = ["first"]
|
||||
json_string_fields = ["last"]
|
||||
json_query = "obj.friends"
|
||||
```
|
||||
|
||||
Input:
|
||||
```json
|
||||
{
|
||||
"obj": {
|
||||
"name": {"first": "Tom", "last": "Anderson"},
|
||||
"age":37,
|
||||
"children": ["Sara","Alex","Jack"],
|
||||
"fav.movie": "Deer Hunter",
|
||||
"friends": [
|
||||
{"first": "Dale", "last": "Murphy", "age": 44},
|
||||
{"first": "Roger", "last": "Craig", "age": 68},
|
||||
{"first": "Jane", "last": "Murphy", "age": 47}
|
||||
]
|
||||
}
|
||||
}
|
||||
```
|
||||
|
||||
Output:
|
||||
```
|
||||
file,first=Dale last="Murphy",age=44
|
||||
file,first=Roger last="Craig",age=68
|
||||
file,first=Jane last="Murphy",age=47
|
||||
```
|
||||
|
||||
[gjson]: https://github.com/tidwall/gjson
|
||||
[gjson syntax]: https://github.com/tidwall/gjson#path-syntax
|
||||
[json]: https://www.json.org/
|
||||
[time parse]: https://golang.org/pkg/time/#Parse
|
|
@ -0,0 +1,34 @@
|
|||
# Logfmt
|
||||
|
||||
The `logfmt` data format parses data in [logfmt] format.
|
||||
|
||||
[logfmt]: https://brandur.org/logfmt
|
||||
|
||||
### Configuration
|
||||
|
||||
```toml
|
||||
[[inputs.file]]
|
||||
files = ["example"]
|
||||
|
||||
## 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 = "logfmt"
|
||||
|
||||
## Set the name of the created metric, if unset the name of the plugin will
|
||||
## be used.
|
||||
metric_name = "logfmt"
|
||||
```
|
||||
|
||||
### Metrics
|
||||
|
||||
Each key/value pair in the line is added to a new metric as a field. The type
|
||||
of the field is automatically determined based on the contents of the value.
|
||||
|
||||
### Examples
|
||||
|
||||
```
|
||||
- method=GET host=example.org ts=2018-07-24T19:43:40.275Z connect=4ms service=8ms status=200 bytes=1653
|
||||
+ logfmt method="GET",host="example.org",ts="2018-07-24T19:43:40.275Z",connect="4ms",service="8ms",status=200i,bytes=1653i
|
||||
```
|
|
@ -0,0 +1,17 @@
|
|||
# Nagios
|
||||
|
||||
The `nagios` data format parses the output of nagios plugins.
|
||||
|
||||
### Configuration
|
||||
|
||||
```toml
|
||||
[[inputs.exec]]
|
||||
## Commands array
|
||||
commands = ["/usr/lib/nagios/plugins/check_load -w 5,6,7 -c 7,8,9"]
|
||||
|
||||
## 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 = "nagios"
|
||||
```
|
|
@ -0,0 +1,36 @@
|
|||
# Value
|
||||
|
||||
The "value" data format translates single values into Telegraf metrics. This
|
||||
is done by assigning a measurement name and setting a single field ("value")
|
||||
as the parsed metric.
|
||||
|
||||
### Configuration
|
||||
|
||||
You **must** tell Telegraf what type of metric to collect by using the
|
||||
`data_type` configuration option. Available options are:
|
||||
|
||||
1. integer
|
||||
2. float or long
|
||||
3. string
|
||||
4. boolean
|
||||
|
||||
**Note:** It is also recommended that you set `name_override` to a measurement
|
||||
name that makes sense for your metric, otherwise it will just be set to the
|
||||
name of the plugin.
|
||||
|
||||
```toml
|
||||
[[inputs.exec]]
|
||||
## Commands array
|
||||
commands = ["cat /proc/sys/kernel/random/entropy_avail"]
|
||||
|
||||
## override the default metric name of "exec"
|
||||
name_override = "entropy_available"
|
||||
|
||||
## 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 = "value"
|
||||
data_type = "integer" # required
|
||||
```
|
||||
|
|
@ -0,0 +1,20 @@
|
|||
# Wavefront
|
||||
|
||||
Wavefront Data Format is metrics are parsed directly into Telegraf metrics.
|
||||
For more information about the Wavefront Data Format see
|
||||
[here](https://docs.wavefront.com/wavefront_data_format.html).
|
||||
|
||||
### Configuration
|
||||
|
||||
There are no additional configuration options for Wavefront Data Format line-protocol.
|
||||
|
||||
```toml
|
||||
[[inputs.file]]
|
||||
files = ["example"]
|
||||
|
||||
## 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 = "wavefront"
|
||||
```
|
|
@ -0,0 +1,46 @@
|
|||
# Example
|
||||
|
||||
This description explains at a high level what the serializer does and
|
||||
provides links to where additional information about the format can be found.
|
||||
|
||||
### Configuration
|
||||
|
||||
This section contains the sample configuration for the serializer. Since the
|
||||
configuration for a serializer is not have a standalone plugin, use the `file`
|
||||
or `http` outputs as the base config.
|
||||
|
||||
```toml
|
||||
[[inputs.file]]
|
||||
files = ["stdout"]
|
||||
|
||||
## Describe variables using the standard SampleConfig style.
|
||||
## https://github.com/influxdata/telegraf/wiki/SampleConfig
|
||||
example_option = "example_value"
|
||||
|
||||
## Data format to output.
|
||||
## 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 = "example"
|
||||
```
|
||||
|
||||
#### example_option
|
||||
|
||||
If an option requires a more expansive explanation than can be included inline
|
||||
in the sample configuration, it may be described here.
|
||||
|
||||
### Metrics
|
||||
|
||||
The optional Metrics section contains details about how the serializer converts
|
||||
Telegraf metrics into output.
|
||||
|
||||
### Example
|
||||
|
||||
The optional Example section can show an example conversion to the output
|
||||
format using InfluxDB Line Protocol as the reference format.
|
||||
|
||||
For line delimited text formats a diff may be appropriate:
|
||||
```diff
|
||||
- cpu,host=localhost,source=example.org value=42
|
||||
+ cpu|host=localhost|source=example.org|value=42
|
||||
```
|
|
@ -0,0 +1,51 @@
|
|||
# Graphite
|
||||
|
||||
The Graphite data format is translated from Telegraf Metrics using either the
|
||||
template pattern or tag support method. You can select between the two
|
||||
methods using the [`graphite_tag_support`](#graphite-tag-support) option. When set, the tag support
|
||||
method is used, otherwise the [Template Pattern][templates]) is used.
|
||||
|
||||
### Configuration
|
||||
|
||||
```toml
|
||||
[[outputs.file]]
|
||||
## Files to write to, "stdout" is a specially handled file.
|
||||
files = ["stdout", "/tmp/metrics.out"]
|
||||
|
||||
## Data format to output.
|
||||
## 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_OUTPUT.md
|
||||
data_format = "graphite"
|
||||
|
||||
## Prefix added to each graphite bucket
|
||||
prefix = "telegraf"
|
||||
## Graphite template pattern
|
||||
template = "host.tags.measurement.field"
|
||||
|
||||
## Support Graphite tags, recommended to enable when using Graphite 1.1 or later.
|
||||
# graphite_tag_support = false
|
||||
```
|
||||
|
||||
#### graphite_tag_support
|
||||
|
||||
When the `graphite_tag_support` option is enabled, the template pattern is not
|
||||
used. Instead, tags are encoded using
|
||||
[Graphite tag support](http://graphite.readthedocs.io/en/latest/tags.html)
|
||||
added in Graphite 1.1. The `metric_path` is a combination of the optional
|
||||
`prefix` option, measurement name, and field name.
|
||||
|
||||
The tag `name` is reserved by Graphite, any conflicting tags and will be encoded as `_name`.
|
||||
|
||||
**Example Conversion**:
|
||||
```
|
||||
cpu,cpu=cpu-total,dc=us-east-1,host=tars usage_idle=98.09,usage_user=0.89 1455320660004257758
|
||||
=>
|
||||
cpu.usage_user;cpu=cpu-total;dc=us-east-1;host=tars 0.89 1455320690
|
||||
cpu.usage_idle;cpu=cpu-total;dc=us-east-1;host=tars 98.09 1455320690
|
||||
```
|
||||
|
||||
#### templates
|
||||
|
||||
Consult the [Template Patterns](/docs/TEMPLATE_PATTERN.md) documentation for
|
||||
details.
|
|
@ -0,0 +1,34 @@
|
|||
# Influx
|
||||
|
||||
The `influx` data format outputs metrics into [InfluxDB Line Protocol][line
|
||||
protocol]. This is the recommended format unless another format is required
|
||||
for interoperability.
|
||||
|
||||
### Configuration
|
||||
```toml
|
||||
[[outputs.file]]
|
||||
## Files to write to, "stdout" is a specially handled file.
|
||||
files = ["stdout", "/tmp/metrics.out"]
|
||||
|
||||
## Data format to output.
|
||||
## 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_OUTPUT.md
|
||||
data_format = "influx"
|
||||
|
||||
## Maximum line length in bytes. Useful only for debugging.
|
||||
influx_max_line_bytes = 0
|
||||
|
||||
## When true, fields will be output in ascending lexical order. Enabling
|
||||
## this option will result in decreased performance and is only recommended
|
||||
## when you need predictable ordering while debugging.
|
||||
influx_sort_fields = false
|
||||
|
||||
## When true, Telegraf will output unsigned integers as unsigned values,
|
||||
## i.e.: `42u`. You will need a version of InfluxDB supporting unsigned
|
||||
## integer values. Enabling this option will result in field type errors if
|
||||
## existing data has been written.
|
||||
influx_uint_support = false
|
||||
```
|
||||
|
||||
[line protocol]: https://docs.influxdata.com/influxdb/latest/write_protocols/line_protocol_tutorial/
|
|
@ -0,0 +1,77 @@
|
|||
# JSON
|
||||
|
||||
The `json` output data format converts metrics into JSON documents.
|
||||
|
||||
### Configuration
|
||||
|
||||
```toml
|
||||
[[outputs.file]]
|
||||
## Files to write to, "stdout" is a specially handled file.
|
||||
files = ["stdout", "/tmp/metrics.out"]
|
||||
|
||||
## Data format to output.
|
||||
## 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_OUTPUT.md
|
||||
data_format = "json"
|
||||
|
||||
## The resolution to use for the metric timestamp. Must be a duration string
|
||||
## such as "1ns", "1us", "1ms", "10ms", "1s". Durations are truncated to
|
||||
## the power of 10 less than the specified units.
|
||||
json_timestamp_units = "1s"
|
||||
```
|
||||
|
||||
### Examples:
|
||||
|
||||
Standard form:
|
||||
```json
|
||||
{
|
||||
"fields": {
|
||||
"field_1": 30,
|
||||
"field_2": 4,
|
||||
"field_N": 59,
|
||||
"n_images": 660
|
||||
},
|
||||
"name": "docker",
|
||||
"tags": {
|
||||
"host": "raynor"
|
||||
},
|
||||
"timestamp": 1458229140
|
||||
}
|
||||
```
|
||||
|
||||
When an output plugin needs to emit multiple metrics at one time, it may use
|
||||
the batch format. The use of batch format is determined by the plugin,
|
||||
reference the documentation for the specific plugin.
|
||||
```json
|
||||
{
|
||||
"metrics": [
|
||||
{
|
||||
"fields": {
|
||||
"field_1": 30,
|
||||
"field_2": 4,
|
||||
"field_N": 59,
|
||||
"n_images": 660
|
||||
},
|
||||
"name": "docker",
|
||||
"tags": {
|
||||
"host": "raynor"
|
||||
},
|
||||
"timestamp": 1458229140
|
||||
},
|
||||
{
|
||||
"fields": {
|
||||
"field_1": 30,
|
||||
"field_2": 4,
|
||||
"field_N": 59,
|
||||
"n_images": 660
|
||||
},
|
||||
"name": "docker",
|
||||
"tags": {
|
||||
"host": "raynor"
|
||||
},
|
||||
"timestamp": 1458229140
|
||||
}
|
||||
]
|
||||
}
|
||||
```
|
Loading…
Reference in New Issue