Manage and Run AI/ML Models as OCI Artifacts with ORAS

Dive deep into the world of cloud-native AI/ML model management! In this video, we'll explore how to leverage ORAS and OCI to streamline your AI/ML workflows. Here's what we'll cover: * *What are ORAS & OCI?* We'll start with a clear explanation of these essential technologies. * *Challenges of managing AI/ML Models in a cloud-native world:* Understand the complexities and pain points of deploying and managing AI/ML models in modern cloud environments. * *How to package an Ollama model as an OCI artifact:* Learn step-by-step how to containerize your Ollama models. * *Manage Ollama models as OCI Artifacts in an OCI registry:* Discover how to store, version, and distribute your models using OCI registries. * *Create a PV & PVC to mount the OCI artifact as a volume in Kubernetes (latest alpha feature):* Get hands-on experience with the cutting-edge Kubernetes feature that enables direct mounting of OCI artifacts as volumes. * *Deploy Ollama in a Pod and mount the model from the OCI registry:* See how to seamlessly integrate your containerized models into your Kubernetes deployments. * *Verify the Ollama model inside the container:* Ensure your model is correctly deployed and accessible. *Benefits:* * Learn how containerization and OCI artifacts simplify AI/ML model lifecycle management, versioning, and portability. * Stay ahead of the curve by adopting best practices for managing AI/ML models in a modern, cloud-native infrastructure. This video is perfect for developers and DevOps engineers looking to enhance their AI/ML deployment strategies in a Kubernetes environment.