Lyft open-sources ‘Flyte’ tool for managing machine learning workflows

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Image Source: https://eng.lyft.com/

Just after Uber open-sourced its debugging tool ‘Manifold’, Lyft open sources its debugging tool ‘Flyte’ for managing machine learning workflows. Lyft describes ‘Flyte as a “structured and distributed platform for concurrent, scalable, and maintainable machine learning workflows.” ‘Flyte’ is built to en-power and speedup machine learning models and data orchestration to be compatible with the latest products and applications.

Flyte comes with Flytekit — a Python SDK to develop applications on Flyte to allow contributors to provide rapid integrations with new services or systems. Apart from Flytekit, ‘Flyte’ also provides backend plugins which can be used to create and manage Kubernetes resources, including CRDs like Spark-on-k8s, or any remote system like Amazon Sagemaker, Qubole, BigQuery, and more.

Features of ‘Flyte’

Github: https://github.com/lyft/flyte

Docs: https://lyft.github.io/flyte

Lyft Blog: https://eng.lyft.com/introducing-flyte-cloud-native-machine-learning-and-data-processing-platform-fb2bb3046a59

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