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Prometheus output data format

content/telegraf/v1/data_formats/output/prometheus.md

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Use the prometheus output data format (serializer) to convert Telegraf metrics into the Prometheus text exposition format.

When used with the prometheus input plugin, set metric_version = 2 in the input to properly round-trip metrics.

Configuration

toml
[[outputs.file]]
  files = ["stdout"]
  data_format = "prometheus"

  ## Optional: Enable batch serialization for improved efficiency.
  ## This is an output plugin option that affects how the serializer
  ## receives metrics.
  # use_batch_format = false

  ## Serializer options (prometheus-specific)
  # prometheus_export_timestamp = false
  # prometheus_sort_metrics = false
  # prometheus_string_as_label = false
  # prometheus_compact_encoding = false

Serializer options

OptionTypeDefaultDescription
prometheus_export_timestampbooleanfalseInclude timestamp on each sample
prometheus_sort_metricsbooleanfalseSort metric families and samples (useful for debugging)
prometheus_string_as_labelbooleanfalseConvert string fields to labels
prometheus_compact_encodingbooleanfalseOmit HELP metadata to reduce payload size

Metric type mappings

Use prometheus_metric_types to explicitly set metric types, overriding Telegraf's automatic type detection. Supports glob patterns.

toml
[[outputs.file]]
  files = ["stdout"]
  data_format = "prometheus"

  [outputs.file.prometheus_metric_types]
    counter = ["*_total", "*_count"]
    gauge = ["*_current", "*_ratio"]

Metric naming

Prometheus metric names are created by joining the measurement name with the field key.

Special case: When the measurement name is prometheus, it is not included in the final metric name.

Labels

Prometheus labels are created from Telegraf tags. String fields are ignored by default and do not produce Prometheus metrics. Set prometheus_string_as_label = true to convert string fields to labels. Set log_level = "trace" to see serialization issues.

Histograms and summaries

Histogram and summary metrics require special consideration. These metric types accumulate state across observations:

  • Histograms count observations in configurable buckets
  • Summaries calculate quantiles over a sliding time window

Use prometheus_client for histograms and summaries

Serializers process metrics in batches and have no memory of previous batches. When histogram or summary data arrives across multiple batches, the serializer cannot combine them correctly.

For example, a histogram with 10 buckets might arrive as:

  • Batch 1: buckets 1-5
  • Batch 2: buckets 6-10

The serializer outputs each batch independently, producing two incomplete histograms instead of one complete histogram.

The prometheus_client output plugin maintains metric state in memory and produces correct output regardless of batch boundaries.

toml
# Recommended for histogram/summary metrics
[[outputs.prometheus_client]]
  listen = ":9273"

Use the serializer for counters and gauges

For counters and gauges, the prometheus serializer works well. Enable use_batch_format = true in your output plugin for more efficient output.

toml
[[outputs.file]]
  files = ["stdout"]
  data_format = "prometheus"
  use_batch_format = true