telegraf/plugins/aggregators/histogram

Histogram Aggregator Plugin

The histogram aggregator plugin creates histograms containing the counts of field values within a range.

If cumulative is set to true, values added to a bucket are also added to the larger buckets in the distribution. This creates a cumulative histogram. Otherwise, values are added to only one bucket, which creates an ordinary histogram

Like other Telegraf aggregators, the metric is emitted every period seconds. By default bucket counts are not reset between periods and will be non-strictly increasing while Telegraf is running. This behavior can be changed by setting the reset parameter to true.

Design

Each metric is passed to the aggregator and this aggregator searches histogram buckets for those fields, which have been specified in the config. If buckets are found, the aggregator will increment +1 to the appropriate bucket. Otherwise, it will be added to the +Inf bucket. Every period seconds this data will be forwarded to the outputs.

The algorithm of hit counting to buckets was implemented on the base of the algorithm which is implemented in the Prometheus client.

Configuration

# Configuration for aggregate histogram metrics
[[aggregators.histogram]]
  ## The period in which to flush the aggregator.
  period = "30s"

  ## If true, the original metric will be dropped by the
  ## aggregator and will not get sent to the output plugins.
  drop_original = false

  ## If true, the histogram will be reset on flush instead
  ## of accumulating the results.
  reset = false

  ## Whether bucket values should be accumulated. If set to false, "gt" tag will be added.
  ## Defaults to true.
  cumulative = true

  ## Example config that aggregates all fields of the metric.
  # [[aggregators.histogram.config]]
  #   ## Right borders of buckets (with +Inf implicitly added).
  #   buckets = [0.0, 15.6, 34.5, 49.1, 71.5, 80.5, 94.5, 100.0]
  #   ## The name of metric.
  #   measurement_name = "cpu"

  ## Example config that aggregates only specific fields of the metric.
  # [[aggregators.histogram.config]]
  #   ## Right borders of buckets (with +Inf implicitly added).
  #   buckets = [0.0, 10.0, 20.0, 30.0, 40.0, 50.0, 60.0, 70.0, 80.0, 90.0, 100.0]
  #   ## The name of metric.
  #   measurement_name = "diskio"
  #   ## The concrete fields of metric
  #   fields = ["io_time", "read_time", "write_time"]

The user is responsible for defining the bounds of the histogram bucket as well as the measurement name and fields to aggregate.

Each histogram config section must contain a buckets and measurement_name option. Optionally, if fields is set only the fields listed will be aggregated. If fields is not set all fields are aggregated.

The buckets option contains a list of floats which specify the bucket boundaries. Each float value defines the inclusive upper (right) bound of the bucket. The +Inf bucket is added automatically and does not need to be defined. (For left boundaries, these specified bucket borders and -Inf will be used).

Measurements & Fields:

The postfix bucket will be added to each field key.

• measurement1
  • field1_bucket
  • field2_bucket

Tags:

• cumulative = true (default):
  • le: Right bucket border. It means that the metric value is less than or equal to the value of this tag. If a metric value is sorted into a bucket, it is also sorted into all larger buckets. As a result, the value of <field>_bucket is rising with rising le value. When le is +Inf, the bucket value is the count of all metrics, because all metric values are less than or equal to positive infinity.
• cumulative = false:
  • gt: Left bucket border. It means that the metric value is greater than (and not equal to) the value of this tag.
  • le: Right bucket border. It means that the metric value is less than or equal to the value of this tag.
  • As both gt and le are present, each metric is sorted in only exactly one bucket.

Example Output:

Let assume we have the buckets [0, 10, 50, 100] and the following field values for usage_idle: [50, 7, 99, 12]

With cumulative = true:

cpu,cpu=cpu1,host=localhost,le=0.0 usage_idle_bucket=0i 1486998330000000000  # none
cpu,cpu=cpu1,host=localhost,le=10.0 usage_idle_bucket=1i 1486998330000000000  # 7
cpu,cpu=cpu1,host=localhost,le=50.0 usage_idle_bucket=2i 1486998330000000000  # 7, 12
cpu,cpu=cpu1,host=localhost,le=100.0 usage_idle_bucket=4i 1486998330000000000  # 7, 12, 50, 99
cpu,cpu=cpu1,host=localhost,le=+Inf usage_idle_bucket=4i 1486998330000000000  # 7, 12, 50, 99

With cumulative = false:

cpu,cpu=cpu1,host=localhost,gt=-Inf,le=0.0 usage_idle_bucket=0i 1486998330000000000  # none
cpu,cpu=cpu1,host=localhost,gt=0.0,le=10.0 usage_idle_bucket=1i 1486998330000000000  # 7
cpu,cpu=cpu1,host=localhost,gt=10.0,le=50.0 usage_idle_bucket=1i 1486998330000000000  # 12
cpu,cpu=cpu1,host=localhost,gt=50.0,le=100.0 usage_idle_bucket=2i 1486998330000000000  # 50, 99
cpu,cpu=cpu1,host=localhost,gt=100.0,le=+Inf usage_idle_bucket=0i 1486998330000000000  # none