AWS Certified Generative AI Developer - Professional AIP-C01

By Amazon · Question Mode

QuestionQ15

Testing, Validation, and Troubleshooting

A company is developing a canary deployment strategy for a payment-processing API. The system must support automated, gradual traffic shifting among multiple Amazon Bedrock models based on real-time inference metrics, historical traffic patterns, and service health. The solution must be able to progressively increase traffic to new model versions. It must increase traffic when metrics stay healthy and reduce traffic when performance degrades below acceptable thresholds.

The company needs comprehensive monitoring of inference latency and error rates throughout the deployment phase. The company must also be able to stop deployments and roll back to a previous model version without manual intervention.

Which solution meets these requirements?

Explanation

AWS Step Functions can orchestrate a staged deployment by waiting between traffic changes and using conditional workflow logic after a Lambda function evaluates Amazon CloudWatch metrics. This creates an automated feedback loop: healthy latency and error-rate metrics permit the next traffic increase, while a threshold breach triggers an immediate rollback to the prior model version. Amazon Bedrock Provisioned Throughput supplies dedicated capacity for the model versions being invoked. AWS documents that Step Functions rolling deployments can monitor CloudWatch alarms and automatically route all traffic back to the prior version when an alarm is triggered.

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