Effortless Scalability: Orchestrating Large Language Model Inference with Kubernetes

Explore the intricacies of deploying and orchestrating large open-source inference models on Kubernetes in this 27-minute conference talk from CNCF. Dive into automating the deployment of heavyweight models like Falcon and Llama 2 using Kubernetes Custom Resource Definitions (CRDs) to manage large model files through container images. Learn about streamlining deployment with an HTTP server for inference calls and eliminating manual tuning of deployment parameters with preset configurations. Discover techniques for auto-provisioning GPU nodes based on specific model requirements and empowering users to deploy containerized models effortlessly. Gain insights into dynamic creation of deployment workloads utilizing all GPU nodes through a controller-based approach.

Effortless Scalability: Orchestrating Large Language Model Inference...- Joinal Ahmed & Nirav Kumar