Amazon Web Services exactexam saa-c03 Questions Bank by Rosanna q401 vce pdf

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Exam Name:	AWS Certified Solutions Architect - Associate (SAA-C03)
Exam Code:	SAA-C03 Dumps
Vendor:	Amazon Web Services	Certification:	AWS Certified Associate
Questions:	527 Q&A's	Shared By:	rosanna

Question 32

A solutions architect needs to optimize a large data analytics job that runs on an Amazon EMR cluster. The job takes 13 hours to finish. The cluster has multiple core nodes and worker nodes deployed on large, compute-optimized instances.

After reviewing EMR logs, the solutions architect discovers that several nodes are idle for more than 5 hours while the job is running. The solutions architect needs to optimize cluster performance.

Which solution will meet this requirement MOST cost-effectively?

Options:

Increase the number of core nodes to ensure there is enough processing power to handle the analytics job without any idle time.

Use the EMR managed scaling feature to automatically resize the cluster based on workload.

Migrate the analytics job to a set of AWS Lambda functions. Configure reserved concurrency for the functions.

Migrate the analytics job core nodes to a memory-optimized instance type to reduce the total job runtime.

Discussion

Question 33

A company is planning to run an AI/ML workload on AWS. The company needs to train a model on a dataset that is in Amazon S3 Standard. A model training application requires multiple compute nodes and single-digit millisecond access to the data.

Which solution will meet these requirements in the MOST cost-effective way?

Options:

Move the data to S3 Intelligent-Tiering. Point the model training application to S3 Intelligent-Tiering as the data source.

Add partitions to the S3 bucket by adding random prefixes. Reconfigure the model training application to point to the new prefixes as the data source.

Move the data to S3 Express One Zone. Point the model training application to S3 Express One Zone as the data source.

Move the data to a General Purpose SSD (gp3) Amazon Elastic Block Store (Amazon EBS)volume attached to an Amazon EC2 instance. Point the model training application to the gp3 volume as the data source.

Discussion

Question 34

A company is designing the architecture for a new mobile app that uses the AWS Cloud. The company uses organizational units (OUs) in AWS Organizations to manage its accounts. The company wants to tag Amazon EC2 instances with data sensitivity by using values of sensitive and nonsensitive IAM identities must not be able to delete a tag or create instances without a tag

Which combination of steps will meet these requirements? (Select TWO.)

Options:

In Organizations, create a new tag policy that specifies the data sensitivity tag key and the required values. Enforce the tag values for the EC2 instances Attach the tag policy to the appropriate OU.

In Organizations, create a new service control policy (SCP) that specifies the data sensitivity tag key and the required tag values Enforce the tag values for the EC2 instances. Attach the SCP to the appropriate OU.

Create a tag policy to deny running instances when a tag key is not specified. Create another tag policy that prevents identities from deleting tags Attach the tag policies to the appropriate OU.

Create a service control policy (SCP) to deny creating instances when a tag key is not specified. Create another SCP that prevents identities from deleting tags Attach the SCPs to the appropriate OU.

Create an AWS Config rule to check if EC2 instances use the data sensitivity tag and the specified values. Configure an AWS Lambda function to delete the resource if a noncompliant resource is found.

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Question 35

A company is developing a containerized web application that needs to be highly available and scalable. The application requires access to GPU resources.

Options:

Package the application as an AWS Lambda function in a container image. Use Lambda to run the containerized application on a runtime with GPU access.

Deploy the application container to Amazon Elastic Kubernetes Service (Amazon EKS). Use AWS Fargate to manage compute resources and access to GPU resources.

Deploy the application container to Amazon Elastic Container Registry (Amazon ECR). Use Amazon ECR to run the containerized application with an attached GPU.

Run the application on Amazon EC2 instances from a GPU instance family by using Amazon Elastic Container Service (Amazon ECS) for orchestration.