Minor updates to metrics documentation
This is a follow up to Ic08d4ff78b6fb614b474b956a32eac352a14262a. It enhances an example, fixes a spelling error, and modifies some sentences for better readability. Change-Id: Icfc89edd426ddee6a93be40c5b2f56d9d78fbd0c
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@ -26,18 +26,18 @@ ironic-lib every time. For example::
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from ironic_lib import metrics_utils
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from ironic_lib import metrics_utils
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def my_method():
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def my_method():
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with metrics_utils.get_metrics_logger(__name__).timer():
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with metrics_utils.get_metrics_logger(__name__).timer('my_method'):
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return _do_work()
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return _do_work()
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As a note, these metric collectors do work for custom HardwareManagers as
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As a note, these metric collectors do work for custom HardwareManagers as
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well, however, you may want to metric the portions of a method that determine
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well. However, you may want to metric the portions of a method that determine
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compatability separate from portions of a method that actually do work, in
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compatibility separate from portions of a method that actually do work, in
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order to assure the metrics are relevant and useful on all hardware.
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order to assure the metrics are relevant and useful on all hardware.
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Explicitly sending metrics
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Explicitly sending metrics
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==========================
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==========================
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A feature that may be particularly helpful for deployers writing custom
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A feature that may be particularly helpful for deployers writing custom
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HardwareManagers is the ability to explicitly send metrics. As an example,
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HardwareManagers is the ability to explicitly send metrics. For instance,
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you could add a cleaning step which would retrieve metrics about a device and
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you could add a cleaning step which would retrieve metrics about a device and
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ship them using the provided metrics library. For example::
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ship them using the provided metrics library. For example::
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