Amazon
MLA-C01 · Question #138
An ML engineer needs to deploy four ML models in an Amazon SageMaker inference pipeline. The models were built with different frameworks. The ML engineer also needs to give clients the ability to use
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Deployment and Orchestration of ML Workflows
Question
An ML engineer needs to deploy four ML models in an Amazon SageMaker inference pipeline. The models were built with different frameworks. The ML engineer also needs to give clients the ability to use the invoke_endpoint call to perform inference for each model. Which solution will meet these requirements MOST cost-effectively?
Options
- ACreate a SageMaker multi-model endpoint.
- BCreate a SageMaker multi-container endpoint.
- CCreate multiple SageMaker single-model endpoints.
- DRun a SparkML job to generate multiple endpoints.
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Topics
#SageMaker Endpoints#Multi-Container Endpoints#Model Deployment#Cost Optimization