Prediction Timers

Troubleshoot prediction latency, find bottlenecks and optimize performance

Qwak prediction timers help troubleshoot model prediction latency, measure prediction times, find bottlenecks, and optimize performance.

Configure multiple timers with custom names for clear visibility using either a context manager or a decorator.
After building, deploying and sending inference requests to your model, you can view these timers on the Latency breakdown graph.

See the Qwak prediction timer in the Model Overview

See the Qwak prediction timer in the Model Overview

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Note: The prediction timer graph may display up to 5 timers including the default overall and predict timers. This leave room for additional 3 custom timers.

Configure timers via decorators

Qwak timers may be configured via a function decorates manager, to easily wrap different methods that are called during the prediction process.

from qwak import qwak_timer
from qwak.model.base import QwakModel

class MyModel(QwakModel):
    def build():
        pass

    @qwak_timer("my_custom_timer_name")
    def pre_process(self, df):
        # Perform custom processing
        return df

    def predict(self, df):
        self.pre_process(df)
        return df

Configure timers via context managers

Qwak timers may be configured via a context manager, to easily wrap parts of your code that need measurements.

from qwak import qwak_timer
from qwak.model.base import QwakModel

class MyModel(QwakModel):
    def build():
        pass

    def predict(self, df):
        with qwak_timer("my_custom_timer_name"):
            # Perform custom processing
            df = df + 1

        return df

Default timers

Overall timer

Measure the end to end inference time, starting at the moment a request arrived, until the inference output.

Queue timer

Measures the the time it takes requests to leave the input queue before reaching the model.