Welcome to Ironic-lib!

Overview

Ironic-lib is a library for use by projects under Bare Metal governance only. This documentation is intended for developer use only. If you are looking for documentation for deployers, please see the ironic documentation.

Metrics

Ironic-lib provides a pluggable metrics library as of the 2.0.0 release. Current provided backends are the default, ‘noop’, which discards all data, and ‘statsd’, which emits metrics to a statsd daemon over the network. The metrics backend to be used is configured via CONF.metrics.backend. How this configuration is set in practice may vary by project.

The typical usage of metrics is to initialize and cache a metrics logger, using the get_metrics_logger() method in ironic_lib.metrics_utils, then use that object to decorate functions or create context managers to gather metrics. The general convention is to provide the name of the module as the first argument to set it as the prefix, then set the actual metric name to the method name. For example:

from ironic_lib import metrics_utils

METRICS = metrics_utils.get_metrics_logger(__name__)

@METRICS.timer('my_simple_method')
def my_simple_method(arg, matey):
    pass

def my_complex_method(arg, matey):
    with METRICS.timer('complex_method_pt_1'):
        do_some_work()

    with METRICS.timer('complex_method_pt_2'):
        do_more_work()
There are three different kinds of metrics:
  • Timers measure how long the code in the decorated method or context manager takes to execute, and emits the value as a timer metric. These are useful for measuring performance of a given block of code.
  • Counters increment a counter each time a decorated method or context manager is executed. These are useful for counting the number of times a method is called, or the number of times an event occurs.
  • Gauges return the value of a decorated method as a metric. This is useful when you want to monitor the value returned by a method over time.

Additionally, metrics can be sent directly, rather than using a context manager or decorator, when appropriate. When used in this way, ironic-lib will simply emit the value provided as the requested metric type. For example:

from ironic_lib import metrics_utils

METRICS = metrics_utils.get_metrics_logger(__name__)

def my_node_failure_method(node):
    if node.failed:
        METRICS.send_counter(node.uuid, 1)

The provided statsd backend natively supports all three metric types. For more information about how statsd changes behavior based on the metric type, see statsd metric types

References

Indices and tables