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juliusv 2013-07-05 23:51:30 +02:00
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README.md
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@ -5,7 +5,10 @@ StatsD-Bridge receives StatsD-style metrics and exports them as Prometheus metri
## Overview
To pipe metrics from an existing StatsD environment into Prometheus, configure StatsD's repeater backend to repeat all received packets to a StatsD-Bridge process. This bridge translates StatsD metrics to Prometheus metrics via configured mapping rules.
To pipe metrics from an existing StatsD environment into Prometheus, configure
StatsD's repeater backend to repeat all received packets to a StatsD-Bridge
process. This bridge translates StatsD metrics to Prometheus metrics via
configured mapping rules.
+----------+ +-----------------+ +--------------+
| StatsD |---(UDP repeater)--->| StatsD-Bridge |<---(scrape /metrics)---| Prometheus |
@ -27,7 +30,16 @@ To pipe metrics from an existing StatsD environment into Prometheus, configure S
## Metric Mapping and Configuration
The StatsD-Bridge can be configured to translate specific dot-separated StatsD metrics into labeled Prometheus metrics via a simple mapping language. A mapping definition starts with a line matching the StatsD metric in question, with `*`s acting as wildcards for each dot-separated metric component. The lines following the matching expression must contain one `label="value"` pair each, and at least define the metric name (label name `name`). The Prometheus metric is then constructed from these labels. `$n`-style references in the label value are replaced by the n-th wildcard match in the matching line, starting at 1. Multiple matching definitions are separated by one or more empty lines. The first mapping rule that matches a StatsD metric wins.
The StatsD-Bridge can be configured to translate specific dot-separated StatsD
metrics into labeled Prometheus metrics via a simple mapping language. A
mapping definition starts with a line matching the StatsD metric in question,
with `*`s acting as wildcards for each dot-separated metric component. The
lines following the matching expression must contain one `label="value"` pair
each, and at least define the metric name (label name `name`). The Prometheus
metric is then constructed from these labels. `$n`-style references in the
label value are replaced by the n-th wildcard match in the matching line,
starting at 1. Multiple matching definitions are separated by one or more empty
lines. The first mapping rule that matches a StatsD metric wins.
An example mapping configuration:
@ -44,7 +56,8 @@ An example mapping configuration:
outcome="$3"
job="$1_server"
This would transform these example StatsD metrics into Prometheus metrics as follows:
This would transform these example StatsD metrics into Prometheus metrics as
follows:
test.dispatcher.FooProcessor.send.success
=> dispatcher_events{processor="FooProcessor", action="send", outcome="success", job="test_dispatcher"}
@ -52,9 +65,12 @@ This would transform these example StatsD metrics into Prometheus metrics as fol
foo_product.signup.facebook.failure
=> signup_events{provider="facebook", outcome="failure", job="foo_product_server"}
Metrics that don't match any mapping in the configuration file are translated into Prometheus metrics without any labels and with certain characters escaped (`_` -> `__`; `-` -> `__`; `.` -> `_`).
Metrics that don't match any mapping in the configuration file are translated
into Prometheus metrics without any labels and with certain characters escaped
(`_` -> `__`; `-` -> `__`; `.` -> `_`).
In general, the different metric types are translated as follows, with certain suffixes appended to the Prometheus metric names:
In general, the different metric types are translated as follows, with certain
suffixes appended to the Prometheus metric names:
StatsD gauge -> Prometheus gauge (suffix `_gauge`)