Skip to content

Latest commit

 

History

History
88 lines (55 loc) · 2.86 KB

File metadata and controls

88 lines (55 loc) · 2.86 KB

Kubeflow on EKS

The Kubeflow project is dedicated to making deployments of machine learning (ML) workflows on Kubernetes simple, portable and scalable. Our goal is not to recreate other services, but to provide a straightforward way to deploy best-of-breed open-source systems for ML to diverse infrastructures. Anywhere you are running Kubernetes, you should be able to run Kubeflow.

This pattern deploys the following resources:

  • Creates EKS Cluster Control plane with public endpoint (for demo purpose only) with a managed node group
  • Deploys supporting add-ons: ClusterAutoScaler, AwsLoadBalancerController, VpcCni, CoreDns, KubeProxy, EbsCsiDriver, CertManagerAddOn, KubeStateMetricsAddOn, PrometheusNodeExporterAddOn, AdotCollectorAddOn, AmpAddOn,
  • Deploy Kubeflow on the EKS cluster

Prerequisites:

Ensure that you have installed the following tools on your machine.

  1. aws cli
  2. kubectl
  3. cdk
  4. npm

Deploy EKS Cluster with Amazon EKS Blueprints for CDK

Clone the repository

git clone https://github.com/aws-samples/cdk-eks-blueprints-patterns.git

Updating npm

npm install -g npm@latest

To view patterns and deploy kubeflow pattern

make list
cdk bootstrap
make pattern kubeflow deploy

Verify the resources

Run update-kubeconfig command. You should be able to get the command from CDK output message. More information can be found at https://aws-quickstart.github.io/cdk-eks-blueprints/getting-started/#cluster-access

aws eks update-kubeconfig --name <your cluster name> --region <your region> --role-arn arn:aws:iam::xxxxxxxxx:role/kubeflow-blueprint-kubeflowblueprintMastersRole0C1-saJBO

Let’s verify the resources created by Steps above.

kubectl get nodes # Output shows the EKS Managed Node group nodes

kubectl get ns | kubeflow # Output shows kubeflow namespace

kubectl get pods --namespace=kubeflow-pipelines  # Output shows kubeflow pods

Execute Machine learning jobs on Kubeflow

log into Kubeflow pipeline UI by creating a port-forward to the ml-pipeline-ui service

kubectl port-forward svc/ml-pipeline-ui 9000:80 -n =kubeflow-pipelines

and open this browser: http://localhost:9000/#/pipelines more pipeline examples can be found at https://www.kubeflow.org/docs/components/pipelines/legacy-v1/tutorials/

Cleanup

To clean up your EKS Blueprints, run the following commands:

cdk destroy kubeflow-blueprint 

Disclaimer

This pattern relies on an open source NPM package eks-blueprints-cdk-kubeflow-ext. Please refer to the package npm site for more information. https://www.npmjs.com/package/eks-blueprints-cdk-kubeflow-ext