Exam AWS Certified Machine Learning - Specialty topic 1 question 283 discussion

Offers the least development effort

https://docs.aws.amazon.com/sagemaker/latest/dg/inference-recommender-recommendation-jobs.html

GPT+Claude 3: The Default job type (option A) involves SageMaker running a set of load tests on the recommended instance types, which can provide a quicker result as it takes less time to complete (within 45 minutes). On the other hand, the Advanced job type (option B) involves a custom load test where you have more control over the traffic pattern and requirements for latency and throughput. However, this option may take longer to complete (an average of 2 hours). Given the requirement for the least development effort, option A seems more suitable. It utilizes the Default job type, which is more automated and requires less manual configuration compared to the Advanced job type. Additionally, the shorter completion time aligns better with the goal of minimizing development effort.

Inference recommendations (Default job type) run a set of load tests on the recommended instance types. You can also load test for a serverless endpoint.. You only need to provide a model package Amazon Resource Name (ARN) to launch this type of recommendation job. Inference recommendation jobs complete within 45 minutes. Endpoint recommendations (Advanced job type) are based on a custom load test where you select your desired ML instances or a serverless endpoint, provide a custom traffic pattern, and provide requirements for latency and throughput based on your production requirements. This job takes an average of 2 hours to complete depending on the job duration set and the total number of inference configurations tested.

B. Traffic patterns are known.

It's either A or B. Advanced Job Type recommendations re based on a custom load test where you select your desired ML instances or a serverless endpoint, provide a custom traffic pattern, and provide requirements for latency and throughput based on your production requirements.

since traffic patterns are already known, it should be B.

A. Register the model artifact and container to the SageMaker Model Registry. Use the SageMaker Inference Recommender Default job type. Provide the known traffic pattern for load testing to select the best instance type and configuration based on the workloads. Explanation: SageMaker Model Registry allows you to register and organize your trained models. The SageMaker Inference Recommender Default job type simplifies the process of selecting the best instance type and configuration based on the known traffic pattern. It automatically selects the best instance type for the model. Load testing with the known traffic pattern helps in understanding the actual workloads and selecting the most appropriate instance type and configuration. This approach leverages the capabilities provided by SageMaker without the need for additional infrastructure or open-source tools