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Amazon Web Services Updated SAA-C03 Exam Questions and Answers by sufyan

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Amazon Web Services SAA-C03 Exam Overview :

Exam Name: AWS Certified Solutions Architect - Associate (SAA-C03)
Exam Code: SAA-C03 Dumps
Vendor: Amazon Web Services Certification: AWS Certified Associate
Questions: 999 Q&A's Shared By: sufyan
Question 76

A company is planning to migrate an on-premises online transaction processing (OLTP) database that uses MySQL to an AWS managed database management system. Several reporting and analytics applications use the on-premises database heavily on weekends and at the end of each month. The cloud-based solution must be able to handle read-heavy surges during weekends and at the end of each month.

Which solution will meet these requirements?

Options:

A.

Migrate the database to an Amazon Aurora MySQL cluster. Configure Aurora Auto Scaling to use replicas to handle surges.

B.

Migrate the database to an Amazon EC2 instance that runs MySQL. Use an EC2 instance type that has ephemeral storage. Attach Amazon EBS Provisioned IOPS SSD (io2) volumes to the instance.

C.

Migrate the database to an Amazon RDS for MySQL database. Configure the RDS for MySQL database for a Multi-AZ deployment, and set up auto scaling.

D.

Migrate from the database to Amazon Redshift. Use Amazon Redshift as the database for both OLTP and analytics applications.

Discussion
Question 77

A company is developing a new application that uses a relational database to store user data and application configurations. The company expects the application to have steady user growth. The company expects the database usage to be variable and read-heavy, with occasional writes.

The company wants to cost-optimize the database solution. The company wants to use an AWS managed database solution that will provide the necessary performance.

Which solution will meet these requirements MOST cost-effectively?

Options:

A.

Deploy the database on Amazon RDS. Use Provisioned IOPS SSD storage to ensure consistent performance for read and write operations.

B.

Deploy the database on Amazon Aurora Serveriess to automatically scale the database capacity based on actual usage to accommodate the workload.

C.

Deploy the database on Amazon DynamoDB. Use on-demand capacity mode to automatically scale throughput to accommodate the workload.

D.

Deploy the database on Amazon RDS Use magnetic storage and use read replicas to accommodate the workload

Discussion
Question 78

A company stores several petabytes of data across multiple AWS accounts The company uses AWS Lake Formation to manage its data lake The company's data science team wants to securely share selective data from its accounts with the company’s engineering team for analytical purposes.

Which solution will meet these requirements with the LEAST operational overhead?

Options:

A.

Copy the required data to a common account. Create an 1AM access role in that account Grant access by specifying a permission policy that includes users from the engineering team accounts as trusted entities.

B.

Use the Lake Formation permissions Grant command in each account where the data is stored to allow the required engineering team users to access the data.

C.

Use AWS Data Exchange to privately publish the required data to the required engineering team accounts

D.

Use Lake Formation tag-based access control to authorize and grant cross-account permissions for the required data to the engineering team accounts

Discussion
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Question 79

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:

A.

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

B.

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

C.

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

D.

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

Discussion
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