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Amazon SAP-C01 - AWS Certified Solutions Architect - Professional Certification Exam

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Question #1 (Topic: demo questions)

A company wants to retire its Oracle Solaris NFS storage arrays. The company requires rapid data migration over its internet network connection to a combination of destinations for Amazon S3. Amazon Elastic File System (Amazon EFS), and Amazon FSx lor Windows File Server. The company also requires a full initial copy, as well as incremental transfers of changes until the retirement of the storage arrays. All data must be encrypted and checked for integrity. Whatshould a solutions architect recommend to meet these requirements?

A.
Configure CloudEndure. Create a project and deploy the CloudEndure agent and token to the storage array. Run the migration plan to start the transfer. 
B.
Configure AWS DataSync. Configure the DataSync agent and deploy it to the local network. Create a transfer task and start the transfer. 
C.
Configure the aws S3 sync command. Configure the AWS client on the client side with credentials. Run the sync command to start the transfer. 
D.
Configure AWS Transfer (or FTP. Configure the FTP client with credentials. Script the client to connect and sync to start the transfer.
Correct Answer: B
Explanation:

Correct Answer: B (AWS DataSync). AWS DataSync is the most suitable service because it is purpose-built for high-speed, secure, and automated migration of on-premises file systems (like NFS on Oracle Solaris) to AWS storage services such as Amazon S3, Amazon EFS, and Amazon FSx for Windows File Server. It supports a full initial data transfer followed by incremental synchronization of changed data until the migration is complete, which matches the requirement for continuous updates before retirement of the source system. DataSync also ensures data integrity through automatic verification and encrypts data in transit using TLS, minimizing operational overhead while handling large-scale data movement efficiently over the internet or Direct Connect.
Question #2 (Topic: demo questions)

A company has an application that sells tickets online and experiences bursts of demand every 7 days. The application has a stateless presentation layer running on Amazon EC2. an Oracle database to store unstructured data catalog information, and a backend API layer. The front-end layer uses an Elastic Load Balancer to distribute the load across nine On-Demand Instances over three Availability Zones (AZs). The Oracle database is running on a single EC2 instance. The company is experiencing performance issues when running more than two concurrent campaigns. A solutions architect must design a solution that meets the following requirements:

• Address scalability issues.

• Increase the level of concurrency.

• Eliminate licensing costs.

• Improve reliability.

Which set ofstepsshould the solutions architect take? 

A.
Create an Auto Scaling group for the front end with a combination of On-Demand and Spot Instances to reduce costs. Convert the Oracle database into a single Amazon RDS reserved DB instance. 
B.
Create an Auto Scaling group for the front end with a combination of On-Demand and Spot Instances to reduce costs. Create two additional copies of the database instance, then distribute the databases in separate AZs.
C.
Create an Auto Scaling group for the front end with a combination of On-Demand and Spot Instances to reduce costs. Convert the tablesin the Oracle database into Amazon DynamoDB tables.
D.
Convert the On-Demand Instances into Spot Instances to reduce costs for the front end. Convert the tables in the Oracle database into Amazon DynamoDB tables.
Correct Answer: C
Explanation:
The best solution is to create an Auto Scaling group for the front-end layer using a mix of On-Demand and Spot Instances to handle burst traffic and improve scalability, and migrate the Oracle database to Amazon DynamoDB to eliminate Oracle licensing costs while also improving scalability and concurrency. DynamoDB is a fully managed, serverless NoSQL database that automatically scales to handle high throughput and concurrent workloads, making it ideal for unpredictable traffic spikes. This architecture also improves reliability by removing the single-instance database bottleneck and ensures better performance during campaign bursts without manual capacity planning.
Question #3 (Topic: demo questions)

A company is running an Apache Hadoop cluster on Amazon EC2 instances. The Hadoop cluster stores approximately 100 TB of data for weekly operational reports and allows occasional access for data scientists to retrieve data. The company needs to reduce the cost and operational complexity for storing and serving this data. Which solution meetsthese requirements in the MOST cost-effective manner? 

A.
Move the Hadoop cluster from EC2 instances to Amazon EMR. Allow data access patterns to remain the same. 
B.
Write a script that resizes the EC2 instances to a smaller instance type during downtime and resizes the instances to a larger instance type before the reports are created. 
C.
Move the data to Amazon S3 and use Amazon Athena to query the data for reports. Allow the data scientists to access the data directly in Amazon S3. 
D.
Migrate the data to Amazon DynamoDB and modify the reports to fetch data from DynamoDB. Allow the data scientists to access the data directly in DynamoDB.
Correct Answer: C
Explanation:
The most cost-effective and operationally simple solution is to move the 100 TB dataset from the EC2-based Hadoop cluster to Amazon S3 and use Amazon Athena for querying and generating weekly reports. Amazon S3 provides highly durable, low-cost object storage that eliminates the need to manage Hadoop infrastructure, while Athena allows serverless SQL queries directly on data stored in S3 without requiring any cluster provisioning or maintenance. This significantly reduces operational overhead and cost, especially for infrequent access patterns like weekly reporting and occasional data science queries, while still providing scalable, on-demand analytics capability.
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