Deploy Meta Llama 3.1-8B on AWS Inferentia using Amazon EKS and vLLM

With the rise of large language models (LLMs) like Meta Llama 3.1, there is an increasing need for scalable, reliable, and cost-effective solutions to deploy and serve these models. AWS Trainium and AWS Inferentia based instances, combined with Amazon Elastic Kubernetes Service (Amazon EKS), provide a performant and low cost framework to run LLMs efficiently in a containerized environment.

In this post, we walk through the steps to deploy the Meta Llama 3.1-8B model on Inferentia 2 instances using Amazon EKS.

Solution overview

The steps to implement the solution are as follows:

1. Create the EKS cluster.
2. Set up the Inferentia 2 node group.
3. Install the Neuron device plugin and scheduling extension.
4. Prepare the Docker image.
5. Deploy the Meta Llama 3.18B model.

We also demonstrate how to test the solution and monitor performance, and discuss options for scaling and multi-tenancy.

Prerequisites

Before you begin, make sure you have ...