ironic-python-agent/doc/source/contributor/metrics.rst

.. _metrics:

===============================================
Emitting metrics from Ironic-Python-Agent (IPA)
===============================================

.. warning::
  IPA metrics are deprecated and scheduled for removal at or after the
  2026.1 OpenStack release cycle.

This document describes how to emit metrics from IPA, including timers and
counters in code to directly emitting hardware metrics from a custom
HardwareManager.

Overview
========
IPA uses a vendored version of the metrics implementation originally from
ironic-lib, with a few caveats due to the dynamic configuration done at
lookup time. You cannot cache the metrics instance as the MetricsLogger
returned will change after lookup if configs different than the default
setting have been used. This also means that the method decorator
cannot be used in IPA.

Using a context manager
=======================
Using the context manager is the recommended way for sending metrics that time
or count sections of code. However, given that you cannot cache the
MetricsLogger, you have to explicitly call get_metrics_logger() from
every time. For example::

  from ironic_python_agent.metrics_lib import metrics_utils

  def my_method():
      with metrics_utils.get_metrics_logger(__name__).timer('my_method'):
          return _do_work()

As a note, these metric collectors do work for custom HardwareManagers as
well. However, you may want to metric the portions of a method that determine
compatibility separate from portions of a method that actually do work, in
order to assure the metrics are relevant and useful on all hardware.

Explicitly sending metrics
==========================
A feature that may be particularly helpful for deployers writing custom
HardwareManagers is the ability to explicitly send metrics. For instance,
you could add a cleaning step which would retrieve metrics about a device and
ship them using the provided metrics library. For example::

  from ironic_python_agent.metrics_lib import metrics_utils

  def my_cleaning_step():
      for name, value in _get_smart_data():
          metrics_utils.get_metrics_logger(__name__).send_gauge(name, value)