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اختبار شهادة AWS Solutions Architect Associate

السؤال 414 من 539

كل الأسئلة

A company is developing a new machine learning (ML) model solution on AWS. The models are developed as independent microservices that fetch approximately 1 GB of model data from Amazon S3 at startup and load the data into memory. Users access the models through an asynchronous API. Users can send a request or a batch of requests and specify where the results should be sent. The company provides models to hundreds of users. The usage patterns for the models are irregular. Some models could be unused for days or weeks. Other models could receive batches of thousands of requests at a time. Which design should a solutions architect recommend to meet these requirements?

الخيارات

  • A Direct the requests from the API to a Network Load Balancer (NLB). Deploy the models as AWS Lambda functions that are invoked by the NLB.
  • B Direct the requests from the API to an Application Load Balancer (ALB). Deploy the models as Amazon ECS services that read from an Amazon SQS queue. Use AWS App Mesh to scale the ECS cluster based on the SQS queue size.
  • C Direct the requests from the API into an Amazon SQS queue. Deploy the models as AWS Lambda functions that are invoked by SQS events. Use AWS Auto Scaling to increase the number of vCPUs for the Lambda functions based on the SQS queue size.
  • D Direct the requests from the API into an Amazon SQS queue. Deploy the models as Amazon ECS services that read from the queue. Enable Auto Scaling on ECS for both the cluster and service based on the queue size.

النقاشات

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