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Machine Learning Implementation and OperationsmediumMultiple ChoiceObjective-mapped

MLS-C01 Practice Question: Machine Learning Implementation and Operations

A company uses SageMaker to host a model for real-time predictions. The model is updated weekly. To minimize downtime during model updates, what should the company do?

⚠ Common exam trap

Many exam-takers assume that updating the endpoint configuration directly (Option C) is sufficient, but they miss that SageMaker requires a new endpoint configuration object to trigger a safe, rolling update rather than an in-place replacement that can cause downtime.

Answer choices

Why each option matters

Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.

Correct answer & explanation

Create a new endpoint configuration with the new model and update the endpoint to use the new configuration

SageMaker allows you to create a new endpoint configuration with the updated model and then update the existing endpoint to use this new configuration. This triggers a rolling update where SageMaker gradually shifts traffic from the old model to the new one, ensuring zero downtime during the transition. The endpoint remains available throughout the process, and you can roll back quickly if needed by reverting to the previous configuration.

Answer analysis

Option-by-option breakdown

For each option: why learners choose it and why it is or isn't the right answer here.

  • Create a new endpoint configuration with the new model and update the endpoint to use the new configuration

    Why this is correct

    SageMaker supports blue/green deployment by updating endpoint to new configuration, minimizing downtime.

  • Create a second endpoint with the new model and use an Application Load Balancer to route traffic

    Why it's wrong here

    An Application Load Balancer (ALB) cannot directly manage traffic between different versions of a *single logical* SageMaker endpoint. SageMaker provides built-in deployment configurations, such as `UpdateEndpoint` with `DeploymentConfig`, specifically designed to perform blue/green updates and minimise downtime for its endpoints. This option is tempting because ALBs are excellent for routing traffic between distinct application versions or services for zero-downtime deployments, and would be appropriate for routing to entirely separate services or SageMaker endpoints in different regions.

  • Update the existing endpoint configuration with the new model URL

    Why it's wrong here

    Updating endpoint configuration causes a brief downtime while the endpoint is updated.

  • Delete the existing endpoint and create a new one with the updated model

    Why it's wrong here

    This causes downtime during deletion and creation.

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