Documentation

Dropwizard input data format

Use the dropwizard input data format to parse the JSON Dropwizard representation of a single dropwizard metric registry into Telegraf metrics. By default, tags are parsed from metric names as if they were actual InfluxDB line protocol keys (measurement<,tag_set>) which can be overridden by defining a custom template pattern. All field value types are supported, string, number and boolean.

Configuration

[[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:

{
    "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:

{
    "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:

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"

Was this page helpful?

Thank you for your feedback!


Introducing InfluxDB Clustered

A highly available InfluxDB 3.0 cluster on your own infrastructure.

InfluxDB Clustered is a highly available InfluxDB 3.0 cluster built for high write and query workloads on your own infrastructure.

InfluxDB Clustered is currently in limited availability and is only available to a limited group of InfluxData customers. If interested in being part of the limited access group, please contact the InfluxData Sales team.

Learn more
Contact InfluxData Sales

The future of Flux

Flux is going into maintenance mode. You can continue using it as you currently are without any changes to your code.

Flux is going into maintenance mode and will not be supported in InfluxDB 3.0. This was a decision based on the broad demand for SQL and the continued growth and adoption of InfluxQL. We are continuing to support Flux for users in 1.x and 2.x so you can continue using it with no changes to your code. If you are interested in transitioning to InfluxDB 3.0 and want to future-proof your code, we suggest using InfluxQL.

For information about the future of Flux, see the following: