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ACK service controller for Amazon SageMaker
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aws-controllers-k8s/sagemaker-controller
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This repository contains source code for the AWS Controllers for Kubernetes(ACK) service controller for Amazon SageMaker.
Pleaselog issues and feedback on the main AWS Controllers forKubernetes Github project.
For a step-by-step tutorial head over toMachine Learning with the ACK SageMaker Controller
For a step-by-step tutorial on how to use Application Auto Scaling Controller with SageMaker head over toScale SageMaker Workloads with Application Auto Scaling
Head over to thesamples directory and follow the README to create resources.
Head over to thesamples directory in application-autoscaling controller repository and follow the README to create resources.
Head over to theManage Resources In Multiple Regions
Head over to theManage Resources In Multiple AWS Accounts
ACK controllers provide the ability to “adopt” resources that were not originally created by an ACK service controller. For more information, seeAdopting Existing AWS Resources in the ACK documentation.
The following steps demonstrate how to adopt a SageMaker Endpoint.
Save the following sample to a file calledadopt-endpoint-sample.yaml.
apiVersion:services.k8s.aws/v1alpha1kind:AdoptedResourcemetadata:name:adopt-endpoint-samplespec:aws:# resource to adopt, not created by ACKnameOrID:xgboost-endpointkubernetes:group:sagemaker.services.k8s.awskind:Endpointmetadata:# target K8s CR namename:xgboost-endpoint
Submit the CR:
kubectl apply -f adopt-endpoint-sample.yaml
Check that theACK.Adopted condition understatus.conditions isTrue:
kubectl describe adoptedresource adopt-endpoint-sample
Your output should look similar to the following:
---kind:AdoptedResourcemetadata:annotations:kubectl.kubernetes.io/last-applied-configuration:'{"apiVersion":"services.k8s.aws/v1alpha1","kind":"AdoptedResource","metadata":{"annotations":{},"name":"xgboost-endpoint","namespace":"default"},"spec":{"aws":{"nameOrID":"xgboost-endpoint"},"kubernetes":{"group":"sagemaker.services.k8s.aws","kind":"Endpoint","metadata":{"name":"xgboost-endpoint"}}}}'creationTimestamp:'2021-04-27T02:49:14Z'finalizers: -finalizers.services.k8s.aws/AdoptedResourcegeneration:1name:adopt-endpoint-samplenamespace:defaultresourceVersion:'12669876'selfLink:"/apis/services.k8s.aws/v1alpha1/namespaces/default/adoptedresources/adopt-endpoint-sample"uid:35f8fa92-29dd-4040-9d0d-0b07bbd7ca0bspec:aws:nameOrID:xgboost-endpointkubernetes:group:sagemaker.services.k8s.awskind:Endpointmetadata:name:xgboost-endpointstatus:conditions: -status:'True'type:ACK.Adopted
Check that the resource exists in your cluster:
kubectl describe endpoints.sagemaker xgboost-endpoint
For information about migrating resources from the oldSageMaker Operators for Kubernetes to the ACK SageMaker controller, seeMigrate resources to the new SageMaker Operators for Kubernetes in theAmazon SageMaker Developer Guide.
For a list of supported resources, refer to theSageMaker API Reference.
Find the helm charts and controller images on Amazon ECR Public Gallery.
Helm Chart:https://gallery.ecr.aws/aws-controllers-k8s/sagemaker-chart
Controller Image:https://gallery.ecr.aws/aws-controllers-k8s/sagemaker-controller
We welcome community contributions and pull requests.
See ourcontribution guide for more information on how toreport issues, set up a development environment, and submit code.
We adhere to theAmazon Open Source Code of Conduct.
You can also learn more about ourGovernance structure.
This project islicensed under the Apache-2.0 License.
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