AI/ML Infrastructure on AWS: A Production-Ready Blueprint

Deploying ML models to production requires more than just a SageMaker endpoint. Here's the 5-layer architecture I use for every ML deployment. Layer 1: Data Layer (FSx for Lustre + S3) Training data needs high-throughput storage: # Create FSx for Lustre linked to S3 training data aws fsx create-file-system \ --file-system-type LUSTRE \ --storage-capacity 1200 \ --lustre-configuration ImportPath = s3://training-data-bucket FSx for Lustre delivers 100+ GB/s throughput vs S3's ~5 GB/s. Training tha