AWS's premier MLOps platform, significantly updated in 2025/2026 with 'Unified Studio' to merge data engineering, analytics, and ML. It provides enterprise-grad
Amazon SageMaker is AWS's end-to-end ML/AI platform: notebooks to distributed training, model registry to managed endpoints, now unified with data tooling and Bedrock access in SageMaker Unified Studio. It's where AWS-centric enterprises industrialize machine learning.
Pricing: Pure usage-based across compute, endpoints, and storage; no platform fee but real cost-engineering required at scale (published pricing, mid-2026).
Bedrock for consuming foundation models via API; SageMaker for training, fine-tuning, and custom model operations. Most AWS enterprises run both: Bedrock for apps, SageMaker for ML engineering.
Right-size endpoints (serverless/async where viable), shut down idle notebooks, use spot training, and tag everything for attribution. Ungoverned SageMaker is a classic cloud-bill incident.