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As a developer and data scientist at a medium-sized company utilizing Vertex AI / AI Platform, you've updated an Auto ML model and wish to deploy it to production while keeping both the old and new versions active simultaneously. The new version should handle only a small fraction of the traffic. The solution must minimize operational overhead and ensure seamless transition between model versions without downtime. Which two actions should you take? (Choose two)
A
Save the model in a Docker container image for manual deployment
B
Deploy the new model version on the same endpoint as the old version
C
Update the Traffic split percentage to allocate a small portion of traffic to the new version
D
Create a Canary Deployment with Cloud Build to gradually shift traffic
E
Use a separate endpoint for the new model version and manually route traffic