Task Statement 2.3: Describe AWS Infrastructure and Technologies for Building GenAI Applications. AIF-C01 Practice Questions (Page 1)

Questions 1–5

1. 1application · medium

   A company wants to prototype a text-generation feature for their product within two weeks. They have a small team of generalist developers and a limited budget. They need to compare several foundation models quickly without committing to a long-term contract. Which approach best meets these needs?

   • AUse Amazon Bedrock to test multiple models on demand and pay per token
   • BTrain a custom model in SageMaker AI
   • CPurchase provisioned throughput for a single model in Bedrock
   • DDeploy an open-source model on EC2
   Reveal Solution Discussion Select an answer first
2. 2application · medium

   A government agency needs to deploy a GenAI application that processes sensitive citizen data. They require that the data be encrypted in transit and at rest, and that access be controlled through fine-grained IAM policies. Which AWS capability directly addresses these requirements?

   • AAWS Identity and Access Management (IAM) and AWS Key Management Service (KMS)
   • BAmazon Route 53
   • CAWS Auto Scaling
   • DAmazon CloudWatch for monitoring
   Reveal Solution Discussion Select an answer first
4. 3foundation · easy

   Which AWS infrastructure benefit ensures that GenAI applications meet regulatory requirements for data handling?

   • AScalability
   • BPerformance
   • CCompliance
   • DAvailability
   Reveal Solution Discussion Select an answer first
5. 4expert · hard

   A company is using Amazon Bedrock to build a GenAI application. They are concerned about the cost of token-based pricing for their high-volume workload. They also need to ensure that the model's responses are consistent and do not vary due to capacity constraints. Which pricing model should they choose?

   • AProvisioned throughput
   • BSavings Plans
   • COn-demand token-based pricing
   • DSpot pricing
   Reveal Solution Discussion Select an answer first
6. 5expert · hard

   A company is evaluating whether to use a managed GenAI service or build their own model. They have a large dataset and a team of experienced ML engineers. Their primary goal is to have full control over the model's behavior and data, but they are concerned about the cost of training and maintaining the model. Which approach is most aligned with their goal of full control while managing costs?

   • ABuild and train a custom model using Amazon SageMaker AI
   • BDeploy an open-source model on EC2
   • CUse Amazon Bedrock with a foundation model and fine-tune it
   • DUse Amazon Bedrock with a custom model import
   Reveal Solution Discussion Select an answer first