Tecton

Twitter’s Feature Store Journey

apply(meetup) - Feb '22 - 10 minutes

A Feature Store is an essential piece of a production ML system. Twitter’s journey of building Feature Stores began several years ago. Since then, we have gone through multiple iterations of our Feature Store to facilitate creating, organizing, sharing and accessing ML features in production. In this talk we will touch on the key parts of this journey, the move from a virtual to a managed store, and our decision to adopt Feast. We will share our reasoning behind design decisions, the challenges we encountered, and the lessons we learned.
Tzvetelina Tzeneva

Staff ML Engineer

Twitter

Tzvetelina is a Staff ML Engineer in the ML Platform Organization. She is the tech lead of the ML Feature Management team and has worked on building two generations of Feature Stores at Twitter. Prior to Twitter, Tzvetelina worked at TellApart where she built distributed systems infrastructure, data platform and data pipelines for the large scale application of direct response advertising. Outside of work, Tzvetelina is a recreational Aerial Silks instructor.

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Unfortunately, Tecton does not currently support these clouds. We’ll make sure to let you know when this changes!

However, we are currently looking to interview members of the machine learning community to learn more about current trends.

If you’d like to participate, please book a 30-min slot with us here and we’ll send you a $50 amazon gift card in appreciation for your time after the interview.

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Interested in trying Tecton? Leave us your information below and we’ll be in touch.​

Unfortunately, Tecton does not currently support these clouds. We’ll make sure to let you know when this changes!

However, we are currently looking to interview members of the machine learning community to learn more about current trends.

If you’d like to participate, please book a 30-min slot with us here and we’ll send you a $50 amazon gift card in appreciation for your time after the interview.

CTA link

or

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