Meetup #50

Two Tools to get you 90% Operational ML

The MLOps tooling landscape is confusing. There’s a complicated patchwork of products and open-source software that each cover some subset of the infrastructure requirements to get ML to production. In this session - we’ll focus on the two most important platforms: model management platforms and feature stores. Model management platforms such as Kubeflow help you get models to production quickly and reliably. Feature stores help you easily build, use, and deploy features. Together, they cover requirements to get models and data to production - the two most important components of any ML project. In this panel discussion, we’ll be joined by David Aronchick (Co-Founder of Kubeflow), Mike Del Balso (Co-Founder of Tecton) and Willem Pienaar (Creator of Feast). These experts will share their perspective on the challenges of Operational ML and how to build the ideal infrastructure stack for MLOps. They’ll talk about the importance of managing models and data with the same engineering efficiency and best practices that we’ve been applying to application code. They’ll discuss the role of Kubeflow, Feast and Tecton, and share their views on the future of MLOps tooling.

Take-aways

War Stories One thing that we can touch on is the emerging distinction between analytic and operational stacks, best practices here, and the differing requirements on use cases. That split exists both in the data and ML side. May be interesting to dissect.

In this episode

David Aronchick

David Aronchick

Program Manager, Azure Innovations, Azure

David leads works in the Azure Innovation Office on Machine Learning. This means he spends most of my time helping humans to convince machines to be smarter. He am only moderately successful at this. Previously, he led product management for Kubernetes on behalf of Google, launched Google Kubernetes Engine, and co-founded the Kubeflow project. He has also worked at Microsoft, Amazon and Chef and co-founded three startups. When not spending too much time in service of electrons, he can be found on a mountain (on skis), traveling the world (via restaurants) or participating in kid activities, of which there are a lot more than he remembers than when he was that age.

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Michael  Del Balso

Michael Del Balso

CEO & Co-founder, Tecton

Mike is the co-founder of Tecton, where he is focused on building next-generation data infrastructure for Operational ML. Before Tecton, Mike was the PM lead for the Uber Michelangelo ML platform. He was also a product manager at Google where he managed the core ML systems that power Google’s Search Ads business. Previous to that, he worked on Google Maps. He holds a BSc in Electrical and Computer Engineering summa cum laude from the University of Toronto.

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Willem  Pienaar

Willem Pienaar

Co-creator, Feast

Willem is currently a tech lead at Tecton where he leads the development of Feast, an open-source feature store for machine learning. Previously he led the ML platform team at Gojek, the Southeast Asian decacorn, which supports a wide variety of models and handles over 100 million orders every month. His main focus areas are building data and ML platforms, allowing organizations to scale machine learning and drive decision making. In a previous life, Willem founded and sold a networking startup.

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Michael  Del Balso

Michael Del Balso

CEO & Co-founder, Tecton

Mike is the co-founder of Tecton, where he is focused on building next-generation data infrastructure for Operational ML. Before Tecton, Mike was the PM lead for the Uber Michelangelo ML platform. He was also a product manager at Google where he managed the core ML systems that power Google’s Search Ads business.

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Demetrios Brinkmann

Demetrios Brinkmann

Host

Demetrios is one of the main organizers of the MLOps community and currently resides in a small town outside Frankfurt, Germany. He is an avid traveller who taught English as a second language to see the world and learn about new cultures. Demetrios fell into the Machine Learning Operations world, and since, has interviewed the leading names around MLOps, Data Science, and ML. Since diving into the nitty-gritty of Machine Learning Operations he felt a strong calling to explore the ethical issues surrounding ML. When he is not conducting interviews you can find him making stone stacking with his daughter in the woods or playing the ukulele by the campfire.