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.

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