.. _dlc-then-eks-devflow: Deploy Neuron Container on Elastic Kubernetes Service (EKS) ============================================================ .. contents:: Table of Contents :local: :depth: 2 Description ----------- |image| .. |image| image:: /images/dlc-on-eks-dev-flow.png :width: 750 :alt: Neuron developer flow for DLC on ECS :align: middle You can use the Neuron version of the `AWS Deep Learning Containers `_ to run inference on Amazon Elastic Kubernetes Service (EKS). In this developer flow, you set up an EKS cluster with Inf1 instances, create a Kubernetes manifest for your inference service and deploy it to your cluster. This developer flow assumes: 1. The model has already been compiled through :ref:`Compilation with Framework API on EC2 instance ` or through :ref:`Compilation with Sagemaker Neo `. 2. You already set up your container to retrieve it from storage. .. _dlc-then-eks-setenv: Setup Environment ----------------- 1. Install pre-requisits: Follow `these instruction `_ to install or upgrade the *eksctl* command line utility on your local computer. Follow `these instruction `_ to install *kubectl* in the same computer. *kubectl* is a command line tool for working with Kubernetes clusters. 2. Follow the instructions in this `EKS documentation link `_ to set up AWS Inferentia on your EKS cluster. Using the YML deployment manifest shown `in the same link `_, replace the `image` in the `containers` specification with the one you built using :ref:`how-to-build-neuron-container` above. .. note:: Before deploying your task definition to your EKS cluster, make sure to push the image to ECR. Refer to `Pushing a Docker image `_ for more information. Self-managed Kubernetes ~~~~~~~~~~~~~~~~~~~~~~~ Please refer to :ref:`tutorial-k8s-env-setup-for-neuron`. In :ref:`example-deploy-rn50-as-k8s-service`, the container image referenced in the YML manifest is created using :ref:`how-to-build-neuron-container`.