Sagemaker Deploy

Inference pipelines: Unseen data goes into model which makes a prediction

But often we have models feeing into models
Unseen data comes in, is pre-processed, the fed into PCA, output of PCA goes into XGBoost, which makes the final prediction

Real-time inference

Model gets data from S3, model built in ECR and accessed via SageMaker endpoint
SageMaker endpoint. Not accessible outside of AWS, only for internal usage. Have to be authenticated. Called via API

Batch inference

Model gets data from S3, model built in ECR and create a Batch Transform job
Batch job takes a large volume of data, pushes it into the model, makes inferences and stores the output somewhere