pipelines/manifests/kustomize/env/aws
Alex afa829a7db
docs: fix rds documentation link (#7635)
2022-05-18 08:07:26 +00:00
..
OWNERS feat(manifest): add support for Standalone KFP on AWS. Fixes #4337 (#4350) 2020-08-12 18:56:14 -07:00
README.md docs: fix rds documentation link (#7635) 2022-05-18 08:07:26 +00:00
aws-configuration-patch.yaml feat(manifest): add support for Standalone KFP on AWS. Fixes #4337 (#4350) 2020-08-12 18:56:14 -07:00
config refactor(deployment): refactor argo manifests to be overlay on top of upstream (#5273) 2021-03-10 18:20:24 -08:00
kustomization.yaml feat(manifest): add support for Standalone KFP on AWS. Fixes #4337 (#4350) 2020-08-12 18:56:14 -07:00
minio-artifact-secret-patch.env feat(manifest): add support for Standalone KFP on AWS. Fixes #4337 (#4350) 2020-08-12 18:56:14 -07:00
params.env feat(manifest): add support for Standalone KFP on AWS. Fixes #4337 (#4350) 2020-08-12 18:56:14 -07:00
secret.env feat(manifest): add support for Standalone KFP on AWS. Fixes #4337 (#4350) 2020-08-12 18:56:14 -07:00
viewer-pod-template.json feat(manifest): add support for Standalone KFP on AWS. Fixes #4337 (#4350) 2020-08-12 18:56:14 -07:00

README.md

Sample installation

  1. Create an EKS cluster

Run this command to create EKS cluster

eksctl create cluster \
--name AWS-KFP \
--version 1.17 \
--region us-west-2 \
--nodegroup-name linux-nodes \
--node-type m5.xlarge \
--nodes 2 \
--nodes-min 1 \
--nodes-max 4 \
--managed
  1. Prepare S3

Create S3 bucket. Console.

Run this command to create S3 bucket by changing <YOUR_S3_BUCKET_NAME> to your prefer s3 bucket name.

export S3_BUCKET=<YOUR_S3_BUCKET_NAME>
export AWS_REGION=us-west-2
aws s3 mb s3://$S3_BUCKET --region $AWS_REGION
  1. Prepare RDS

Follow this doc to set up AWS RDS instance.

  1. Customize your values
  1. Install
kubectl apply -k ../../cluster-scoped-resources
# If upper one action got failed, e.x. you used wrong value, try delete, fix and apply again
# kubectl delete -k ../../cluster-scoped-resources

kubectl wait crd/applications.app.k8s.io --for condition=established --timeout=60s

kubectl apply -k ./
# If upper one action got failed, e.x. you used wrong value, try delete, fix and apply again
# kubectl delete -k ./

kubectl wait applications/pipeline -n kubeflow --for condition=Ready --timeout=1800s

kubectl port-forward -n kubeflow svc/ml-pipeline-ui 8080:80

Now you can access via localhost:8080