deployment_pipeline

Amazon SageMaker A/B Testing Pipeline

This folder contains the CDK infrastructure for the multi-variant deployment pipeline.

Deployment Pipeline

This deployment pipeline contains a few stages.

1. Source: Pull the latest deployment configuration from AWS CodeCommit repository.
2. Build: AWS CodeBuild job to create the AWS CloudFormation template for deploying the endpoint.
   • Query the Amazon SageMaker project to get the top approved models.
   • Use the AWS CDK to create a CFN stack to deploy multi-variant SageMaker Endpoint.
3. Deploy: Run the AWS CloudFormation stack to create/update the SageMaker endpoint, tagged with properties based on configuration:
   • ab-testing:enabled equals true
   • ab-testing:strategy is one WeightedSampling, EpslionGreedy, UCB1 or ThompsonSampling.
   • ab-testing:epsilon is parameters for EpslionGreedy strategy, defaults to 0.1.
   • ab-testing:warmup the number of invocations to warmup with WeightedSampling strategy, defaults to 0.

Testing

Once you have created a SageMaker Project, you can test the Build stage and Register events locally by setting some environment variables.

Build Stage

Export the environment variables for the SAGEMAKER_PROJECT_NAME and SAGEMAKER_PROJECT_ID created by your SageMaker Project cloud formation. Then run the cdk synth command:

export SAGEMAKER_PROJECT_NAME="<<project_name>>"
export SAGEMAKER_PROJECT_ID="<<project_id>>"
export STAGE_NAME="dev"
cdk synth

Register

Export the environment variable for the REGISTER_LAMBDA created as part of the ab-testing-api stack, then run register.py file.

export REGISTER_LAMBDA="<<register_lambda>>"
python register.py