Building low-overhead metrics collection for high-performance systems

Design decisions that allowed us to capture metrics in Wallaroo with a low-overhead.

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Latency Histograms and Percentile Distributions In Wallaroo Performance Metrics

How we implemented Wallaroo’s low overhead performance counters and the philosophy behind the choices we made.

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A Scikit-learn pipeline in Wallaroo

Creating an inference pipeline with MNIST

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Idiomatic Python Stream Processing in Wallaroo

Wallaroo’s New Python API makes writing distributed stream processing applications more Pythonic.

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Why we wrote our Kafka Client in Pony

Why we wrote our Kafka Client in Pony instead of relying on the existing C Kafka Client and creating bindings for it. We talk about the pros/cons of our decision and how far we’ve come including some preliminary performance numbers.

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