原文文档：http://airflow.apache.org/docs/apache-airflow/stable/logging-monitoring/metrics.html

Airflow can be set up to send metrics to StatsD.

1. Setup

First you must install statsd requirement:

$ pip install 'apache-airflow[statsd]'

Add the following lines to your configuration file e.g. airflow.cfg

[metrics]
statsd_on = True
statsd_host = localhost
statsd_port = 8125
statsd_prefix = airflow

If you want to avoid sending all the available metrics to StatsD, you can configure an allow list of prefixes to send only the metrics that start with the elements of the list:

[metrics]
statsd_allow_list = scheduler,executor,dagrun

If you want to redirect metrics to different name, you can configure stat_name_handler option in [scheduler] section. It should point to a function that validate the statsd stat name, apply changes to the stat name if necessary and return the transformed stat name. The function may looks as follow:

def my_custom_stat_name_handler(stat_name: str) -> str:
    return stat_name.lower()[:32]

If you want to use a custom Statsd client outwith the default one provided by Airflow the following key must be added to the configuration file alongside the module path of your custom Statsd client. This module must be available on your PYTHONPATH.

[metrics]
statsd_custom_client_path = x.y.customclient

See Modules Management for details on how Python and Airflow manage modules.

Note: For a detailed listing of configuration options regarding metrics, see the configuration reference documentation - [metrics].

2. Counters

3. Gauges

4. Timers