Embracing Multi-Tenancy While Scaling MLOps

Explore the challenges and solutions of implementing multi-tenancy in MLOps systems in this 30-minute conference talk from the Cloud Native Computing Foundation (CNCF). Delve into the growing need for efficient resource sharing, isolation, and security across multiple teams as organizations scale their machine learning operations. Learn about fundamental requirements for multi-tenant MLOps environments, including ML workflow isolation, resource quotas, role-based access control, data isolation, and shared artifact repositories. Discover how open-source tools like Flyte can help overcome implementation challenges, enabling different teams to operate independently while sharing resources efficiently and cost-effectively. Gain insights from speakers Shivay Lamba and Rohit Ghumare on creating secure and efficient multi-tenant environments for large-scale ML model training and deployment.