AIP-C01 · Question #55
AIP-C01 Question #55: Real Exam Question with Answer & Explanation
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Question
A company is designing a canary deployment strategy for a payment processing API. The system must support automated gradual traffic shifting between multiple Amazon Bedrock models based on real-time inference metrics, historical traffic patterns, and service health. The solution must be able to gradually increase traffic to new model versions. The system must increase traffic if metrics remain healthy and decrease traffic if the performance degrades below acceptable thresholds. The company needs to comprehensively monitor inference latency and error rates during the deployment phase. The company must also be able to halt deployments and revert to a previous model version without any manual intervention. Which solution will meet these requirements?
Options
- AUse Amazon Bedrock with provisioned throughput to host model versions. Configure an Amazon
- BUse AWS Lambda functions to invoke various Amazon Bedrock model versions. Use an Amazon
- CUse Amazon SageMaker AI endpoint variants to represent multiple Amazon Bedrock model
- DUse Amazon OpenSearch Service to track inference logs. Configure OpenSearch Service to
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