Cloud Deployment: AWS SageMaker
SageMaker Model, EndpointConfig, Endpoint, real-time inference, batch transform.
Why SageMaker
Amazon SageMaker is a managed service for training and deploying ML models. Instead of provisioning servers and load balancers yourself, you describe a model and SageMaker stands up a scalable HTTPS endpoint behind the scenes.
The Three Ingredients
A SageMaker deployment needs three things:
- A container image_uri (your serving image in ECR or a built-in framework image)
- The trained weights as model_data, a tar.gz in S3
- An IAM role granting SageMaker access to those resources