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instrumentation.md

  • Yorick Peterse's avatar
    be3b8784
    Track method call times/counts as a single metric · be3b8784
    Yorick Peterse authored
    Previously we'd create a separate Metric instance for every method call
    that would exceed the method call threshold. This is problematic because
    it doesn't provide us with information to accurately get the _total_
    execution time of a particular method. For example, if the method
    "Foo#bar" was called 4 times with a runtime of ~10 milliseconds we'd end
    up with 4 different Metric instances. If we were to then get the
    average/95th percentile/etc of the timings this would be roughly 10
    milliseconds. However, the _actual_ total time spent in this method
    would be around 40 milliseconds.
    
    To solve this problem we now create a single Metric instance per method.
    This Metric instance contains the _total_ real/CPU time and the call
    count for every instrumented method.
    be3b8784
    History
    Track method call times/counts as a single metric
    Yorick Peterse authored
    Previously we'd create a separate Metric instance for every method call
    that would exceed the method call threshold. This is problematic because
    it doesn't provide us with information to accurately get the _total_
    execution time of a particular method. For example, if the method
    "Foo#bar" was called 4 times with a runtime of ~10 milliseconds we'd end
    up with 4 different Metric instances. If we were to then get the
    average/95th percentile/etc of the timings this would be roughly 10
    milliseconds. However, the _actual_ total time spent in this method
    would be around 40 milliseconds.
    
    To solve this problem we now create a single Metric instance per method.
    This Metric instance contains the _total_ real/CPU time and the call
    count for every instrumented method.
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