Building Foundational ML Platforms with Kubernetes and Kubeflow with Ali Rodell - #595
Analysis
This podcast episode from Practical AI features Ali Rodell, a senior director at Capital One, discussing the development of machine learning platforms. The conversation centers around the use of open-source tools like Kubernetes and Kubeflow, highlighting the importance of a robust open-source ecosystem. The episode explores the challenges of customizing these tools, the need to accommodate diverse user personas, and the complexities of operating in a regulated environment like the financial industry. The discussion provides insights into the practical considerations of building and maintaining ML platforms.
Key Takeaways
- •Open-source tools like Kubernetes and Kubeflow are crucial for building ML platforms.
- •Customization of these tools presents challenges that need to be addressed.
- •Diverse user personas and regulatory environments impact platform design.
“We discuss the importance of a healthy open source tooling ecosystem, Capital One’s use of various open source capabilites like kubeflow and kubernetes to build out platforms, and some of the challenges that come along with modifying/customizing these tools to work for him and his teams.”