Summary and Quiz

Explore how to design and operate production-grade inference on SageMaker by combining high availability, controlled rollouts, instance selection, inference patterns, and scaling. Understand deployment best practices including real-time endpoints setup, model versioning, rolling updates, and optimization techniques for large models. Gain knowledge on autoscaling, monitoring with CloudWatch and Model Monitor, and how to maintain reliability and auditability for machine learning models in production environments.