Infrastructure setup
For the exercises in this chapter, we will need an S3 bucket to store data, an IAM role, and an IAM user that has access to both the SageMaker Feature Store and the S3 bucket. Since we have already gone through creating all these resources, I will skip through this. Please refer to Chapter 4, Adding Feature Store to ML Models, for S3 bucket creation, and Chapter 7, Feast Alternatives and ML Best Practices, for IAM role and IAM user creation. That is all we need, in terms of initial setup for this chapter.
Important Note
I am trying to use as few resources of AWS SageMaker as possible since it will incur costs if your free trial has come to an end. You can use SageMaker Studio for a better experience with notebooks and also the UI of the feature store.