Question
HOTSPOT -
A company wants to host an ML model on Amazon SageMaker. An ML engineer is configuring a continuous integration and continuous delivery (CI/CD) pipeline in AWS CodePipeline to deploy the model. The pipeline must run automatically when new training data for the model is uploaded to an Amazon S3 bucket.
Select and order the pipeline's correct steps from the following list. Each step should be selected one time or not at all. (Select and order three.)
• An S3 event notification invokes the pipeline when new data is uploaded.
• An S3 Lifecycle rule invokes the pipeline when new data is uploaded.
• SageMaker retrains the model by using the data in the S3 bucket.
• The pipeline deploys the model to a SageMaker endpoint.
• The pipeline deploys the model to SageMaker Model Registry.
Explanation
Step 1: An S3 event notification fires when new objects are uploaded, so it can start the pipeline automatically when new training data arrives. S3 Lifecycle rules only transition or expire objects; they cannot invoke a pipeline.
Step 2: SageMaker retrains the model by using the new data in the S3 bucket, so the model reflects the latest data.
Step 3: The pipeline deploys the retrained model to a SageMaker endpoint, which is what hosts the model and serves predictions. Model Registry only catalogs and versions model packages; registering a model there does not host it.
