Machine Learning with Kubernetes
Explore the intersection of MLOps and Kubernetes in this 25-minute conference talk. Dive into the role of Kubernetes in building scalable and resilient machine learning production pipelines. Learn about K8s cluster design for MLOps and discover how Kubernetes acts as a catalyst in MLOps evolution. Examine Kubeflow, an open-source project that simplifies ML workflows on Kubernetes, offering scalability and portability. Investigate major Kubeflow components and their application in addressing MLOps challenges. Gain insights into Istio, a service mesh for Kubernetes, and its impact on enhancing observability, security, and reliability of ML production pipelines. Discover how to leverage Kubeflow and MLFlow for hyperparameter tuning and distributed training, while abstracting away Docker and Kubernetes complexities.