Questão 4 — Simulado AWS Certified AI Practitioner (AIP-C01) – Questões Atualizadas
An ecommerce company is building an internal platform to develop generative AI applications by using Amazon Bedrock foundation models (FMs). Developers need to select models based on evaluations that are aligned to ecommerce use cases. The platform must display accuracy metrics for text generation and summarization in dashboards. The company has custom ecommerce datasets to use as standardized evaluation inputs. Which combination of steps will meet these requirements with the LEAST operational overhead? (Select TWO.)
- A. Import the datasets to an Amazon S3 bucket. Provide appropriate IAM permissions and cross- origin resource sharing (CORS) permissions to give the evaluation jobs access to the datasets.
- B. Import the datasets to an Amazon S3 bucket. Provide appropriate IAM permissions and a VPC endpoint configuration to give the evaluation jobs access to the datasets.
- C. Configure an AWS Lambda function to create model evaluation jobs on a schedule in the Amazon Bedrock console. Provide the URI of the S3 bucket that contains the datasets as an input. Configure the evaluation jobs to measure the real world knowledge (RWK) score for text generation and BERTScore for summarization. Configure a second Lambda function to check the status of the jobs and publish custom logs to Amazon CloudWatch. Create a custom Amazon CloudWatch Logs Insights dashboard.
- D. Use Amazon SageMaker Clarify on a schedule to create model evaluation jobs. Use open source frameworks to create and run standardized evaluations. Publish results to Amazon CloudWatch namespaces. Use an AWS Lambda function to check the status of the jobs and publish custom logs to Amazon CloudWatch. Create a custom Amazon CloudWatch Logs Insights dashboard.
- E. Run an Amazon SageMaker AI notebook job on a schedule by using the fmvelos or ragas framework to run evaluations that use the datasets in the S3 bucket. Write Python code in the notebook that makes direct InvokeModel API calls to the FMs and processes their responses for evaluation. Publish job status and results to Amazon CloudWatch Logs to measure the real world knowledge (RWK) score for text generation and toxicity for summarization as metrics for accuracy. Create a custom CloudWatch Logs Insights dashboard.
Resposta correta:
B, C
Explicação
Explanation: The least operational overhead approach is to use managed Amazon Bedrock model evaluation workflows with datasets stored in Amazon S3, and then publish results into Amazon CloudWatch for dashboards. That is exactly what options B and C combine. Step B correctly places standardized evaluation inputs in Amazon S3 and focuses on granting the evaluation workflow the right permissions to read those datasets. In practice, the key requirement is controlled access to the S3 objects used as evaluation datasets. Establishing IAM permissions and private access patterns (such as using VPC connectivity patterns where applicable to the organization's networking posture) is aligned with enterprise requirements and avoids building custom storage or data distribution systems for evaluators. Step C then operationalizes the evaluation lifecycle with minimal infrastructure: a scheduled AWS Lambda function starts evaluation jobs using the S3 dataset location, and a second Lambda function checks job status and pushes results and operational signals to CloudWatch. This meets the platform requirement to surface accuracy metrics in dashboards because CloudWatch metrics/logs can be visualized in dashboards and queried through CloudWatch Logs Insights. It also supports continuous, standardized comparisons across models without requiring developers to run ad-hoc experiments. The alternatives introduce more operational burden. D and E rely on Amazon SageMaker-based tooling, notebook jobs, and open source evaluation frameworks, which require more environment management, dependency control, scaling considerations, and maintenance over time. A includes CORS, which is primarily a browser-access concern and does not address how Bedrock-managed evaluation jobs securely access S3 in the typical service-to-service pattern. Therefore, B + C achieves standardized model evaluation, automated scheduling, and dashboard- ready observability with the smallest operations footprint.
Quer todas as 119 questões por R$ 198,00?