Q52 — AWS AIF-C01 Ch.1

Question 52 of 100 | ← Chapter 1

A company uses Amazon SageMaker in its production environment for its ML pipeline. Its input data size reaches up to 1 GB, and inference time lasts up to 1 hour. The company requires near-real-time latency. Which SageMaker inference option satisfies these requirements?

• A. Real-time inference ✓
• B. Serverless inference
• C. Asynchronous inference
• D. Batch transform

Correct Answer: A. Real-time inference

Explanation

This question tests knowledge of Amazon SageMaker inference options. Given the requirement for near-real-time latency, a low-latency inference option is needed. Real-time inference (Option A) delivers predictions with low latency, making it suitable for time-sensitive applications. Serverless inference (Option B) auto-scales but does not guarantee real-time performance. Asynchronous inference (Option C) is intended for non-immediate results. Batch transform (Option D) processes large volumes of data offline and is unsuitable for real-time use. Thus, Option A—Real-time inference—is the best fit.