19ad83b6f5
This was the only meaningful documentation from ironic-lib. Change-Id: I8c40433edd0c3664488887034a49f687605093c1
59 lines
2.3 KiB
ReStructuredText
59 lines
2.3 KiB
ReStructuredText
Metrics
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=======
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Ironic provides a pluggable metrics library as of the 2.0.0 release.
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The metrics backend to be used is configured via ``CONF.metrics.backend``.
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Not all backends support all metrics types or metric sources.
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The typical usage of metrics is to initialize and cache a metrics logger,
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using the ``get_metrics_logger()`` method in ``metrics_utils``, then
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use that object to decorate functions or create context managers to gather
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metrics. The general convention is to provide the name of the module as the
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first argument to set it as the prefix, then set the actual metric name to the
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method name. For example:
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.. code-block:: python
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from ironic import metrics_utils
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METRICS = metrics_utils.get_metrics_logger(__name__)
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@METRICS.timer('my_simple_method')
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def my_simple_method(arg, matey):
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pass
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def my_complex_method(arg, matey):
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with METRICS.timer('complex_method_pt_1'):
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do_some_work()
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with METRICS.timer('complex_method_pt_2'):
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do_more_work()
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There are three different kinds of metrics:
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- **Timers** measure how long the code in the decorated method or context
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manager takes to execute, and emits the value as a timer metric. These
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are useful for measuring performance of a given block of code.
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- **Counters** increment a counter each time a decorated method or context
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manager is executed. These are useful for counting the number of times a
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method is called, or the number of times an event occurs.
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- **Gauges** return the value of a decorated method as a metric. This is
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useful when you want to monitor the value returned by a method over time.
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Additionally, metrics can be sent directly, rather than using a context
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manager or decorator, when appropriate. When used in this way, we will
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simply emit the value provided as the requested metric type. For example:
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.. code-block:: python
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from ironic import metrics_utils
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METRICS = metrics_utils.get_metrics_logger(__name__)
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def my_node_failure_method(node):
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if node.failed:
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METRICS.send_counter(node.uuid, 1)
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The provided statsd backend natively supports all three metric types. For more
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information about how statsd changes behavior based on the metric type, see
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`statsd metric types <https://github.com/etsy/statsd/blob/master/docs/metric_types.md>`_
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