MLS-C01 · Question #248
A manufacturing company wants to monitor its devices for anomalous behavior. A data scientist has trained an Amazon SageMaker scikit-learn model that classifies a device as normal or anomalous based…
The correct answer is A. SageMaker Batch Transform. https://docs.aws.amazon.com/sagemaker/latest/dg/inference-cost-optimization.html "Use batch inference for workloads for which you need inference for a large set of data for processes that happen offline (that is, you don't need a persistent endpoint). You pay for the instance…
Question
A manufacturing company wants to monitor its devices for anomalous behavior. A data scientist has trained an Amazon SageMaker scikit-learn model that classifies a device as normal or anomalous based on its 4-day telemetry. The 4-day telemetry of each device is collected in a separate file and is placed in an Amazon S3 bucket once every hour. The total time to run the model across the telemetry for all devices is 5 minutes. What is the MOST cost-effective solution for the company to use to run the model across the telemetry for all the devices?
Options
- ASageMaker Batch Transform
- BSageMaker Asynchronous Inference
- CSageMaker Processing
- DA SageMaker multi-container endpoint
How the community answered
(23 responses)- A74% (17)
- B4% (1)
- C13% (3)
- D9% (2)
Explanation
https://docs.aws.amazon.com/sagemaker/latest/dg/inference-cost-optimization.html "Use batch inference for workloads for which you need inference for a large set of data for processes that happen offline (that is, you don't need a persistent endpoint). You pay for the instance for the duration of the batch inference job". As you pay for the batch job duration, cost should not be an issue with Batch transform. "Use asynchronous inference for asynchronous workloads that process up to 1 GB of data (such as text corpus, image, video, and audio) that are latency insensitive and cost sensitive. With asynchronous inference, you can control costs by specifying a fixed number of instances for the optimal processing rate instead of provisioning for the peak. You can also scale down to zero to save additional costs."
Topics
Community Discussion
No community discussion yet for this question.