Description: Deploy the development Amazon SageMaker Endpoint.
Parameters:
  ImageRepoUri:
    Type: String
    Description: Uri of the docker (ECR) model image
  ModelName:
    Type: String
    Description: Name of the model
  TrainJobId:
    Type: String
    Description: Id of the Codepipeline + SagemakerJobs
  DeployRoleArn:
    Type: String
    Description: The role for executing the deployment
  ModelVariant:
    Type: String
    Description: Name of the endpoint variant
  KmsKeyId:
    Description: AWS KMS key ID used to encrypt data at rest on the ML storage volume attached to endpoint config.
    Type: String

Resources:
  Model:
    Type: "AWS::SageMaker::Model"
    Properties:
      ModelName: !Sub ${ModelName}-dev-${TrainJobId}
      PrimaryContainer:
        Image: !Ref ImageRepoUri
        ModelDataUrl: !Sub s3://sagemaker-${AWS::Region}-${AWS::AccountId}/${ModelName}/${ModelName}-${TrainJobId}/output/model.tar.gz
      ExecutionRoleArn: !Ref DeployRoleArn

  EndpointConfig:
    Type: "AWS::SageMaker::EndpointConfig"
    Properties:
      ProductionVariants:
        - InitialInstanceCount: 1
          InitialVariantWeight: 1.0
          InstanceType: ml.t2.medium
          ModelName: !GetAtt Model.ModelName
          VariantName: !Sub ${ModelVariant}-${ModelName}
      EndpointConfigName: !Sub ${ModelName}-dec-${TrainJobId}
      KmsKeyId: !Ref KmsKeyId

  Endpoint:
    Type: "AWS::SageMaker::Endpoint"
    Properties:
      EndpointName: !Sub ${ModelName}-dev-${TrainJobId}
      EndpointConfigName: !GetAtt EndpointConfig.EndpointConfigName