Object Storage Driven Machine Learning Workloads

Explore the intersection of object storage and machine learning in this 24-minute conference talk. Discover how AI-first architectures are leveraging object storage, with ML frameworks like Tensorflow and Kubeflow utilizing the S3 API for model, data, and artifact interactions. Learn about the benefits of object storage, including scalability, performance, immutability, and lifecycle features. Gain insights into tiering models and data across Kubernetes-native object storage classes and replicating between datacenters, edge, and cloud environments. Follow along as the speaker demonstrates deploying open-source MinIO and Tensorflow on Kubernetes, and learn how to build and operate a secure data pipeline while automating ML testing and operations.

Object Storage Driven Machine Language Workloads - Daniel Valdivia, MinIO