What is Amazon SageMaker?
SageMaker brings together tools for data prep, training, tuning, and hosting models. It supports traditional ML and GenAI, and integrates with the wider AWS stack for security and scale.
How does it work?
Use managed notebooks and pipelines, train on your data, deploy endpoints, and monitor cost and quality. Combine with Bedrock for foundation models when needed.
When does it matter? (Examples)
- You train custom models on proprietary data.
- You want managed hosting and monitoring for production workloads.
- You need MLOps pipelines with approvals and traceability.
Benefits
- Accelerates experimentation
- Manages deployment at scale
- Integrates with AWS security
Risks
- Service sprawl without standards
- Cost surprises from large jobs
- Complexity for small teams
Antire and Amazon SageMaker
We design right‑sized ML/GenAI pipelines on AWS, balancing speed and governance, and connecting outcomes to business KPIs.
Services
Related words
Amazon Bedrock, Training, Inference, Feature store, MLOps, RAG