A company runs Amazon SageMaker ML models that use accelerated instances. The models require real-time responses. Each model has different scaling requirements. The company must not allow a cold start for the models.
Which solution will meet these requirements?
✅ Explanation: Requirements Recap: Real-time inference: Needs low-latency predictions. Accelerated instances: Likely GPU-backed, costly to scale inefficiently. No cold starts: Endpoints must always be warm and responsive. Each model has different scaling needs: Must support independent scaling of each model. ✅ Why Option C is correct: Inference components are a new SageMaker feature that allow: Hosting multiple models on a single endpoint. Independent scaling of each model (component). Avoiding cold starts via minimum number of copies. Setting min invocations or min replicas ≥ 1 keeps the model always warm, eliminating cold starts. This solution meets all requirements efficiently.
this is correct