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

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’



Lyft Blog:

Asif Razzaq is an AI Journalist and Cofounder of Marktechpost, LLC. He is a visionary, entrepreneur and engineer who aspires to use the power of Artificial Intelligence for good.

Asif's latest venture is the development of an Artificial Intelligence Media Platform (Marktechpost) that will revolutionize how people can find relevant news related to Artificial Intelligence, Data Science and Machine Learning.

Asif was featured by Onalytica in it’s ‘Who’s Who in AI? (Influential Voices & Brands)’ as one of the 'Influential Journalists in AI' ( His interview was also featured by Onalytica (