This document describes how to emit metrics from IPA, including timers and counters in code to directly emitting hardware metrics from a custom HardwareManager.
IPA uses the metrics implementation 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 supported by ironic-lib cannot be used in IPA.
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 ironic-lib every time. For example:
from ironic_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.
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_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)
For more information, please read the source of the metrics module in ironic-lib.