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AWS Certified Professional AWS Certified Solutions Architect - Professional

AWS Certified Solutions Architect - Professional

Last Update Mar 2, 2026
Total Questions : 625

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Questions 2

A company runs a processing engine in the AWS Cloud. The engine processes environmental data from logistics centers to calculate a sustainability index. The company has millions of devices in logistics centers that are spread across Europe. The devices send information to the processing engine through a RESTful API. The API experiences unpredictable bursts of traffic. The company must implement a solution to process all data that the devices send to the processing engine. Data loss is unacceptable. Which solution will meet these requirements?

Options:

A.  

Create an Application Load Balancer (ALB) for the RESTful API. Create an Amazon SQS queue. Create a listener and a target group for the ALB. Add the SQS queue as the target. Use a container that runs in Amazon ECS with the Fargate launch type to process messages in the queue.

B.  

Create an Amazon API Gateway HTTP API that implements the RESTful API. Create an Amazon SQS queue. Create an API Gateway service integration with the SQS queue. Create an AWS Lambda function to process messages in the SQS queue.

C.  

Create an Amazon API Gateway REST API that implements the RESTful API. Create a fleet of Amazon EC2 instances in an Auto Scaling group. Create an API Gateway Auto Scaling group proxy integration. Use the EC2 instances to process incoming data.

D.  

Create an Amazon CloudFront distribution for the RESTful API. Create a data stream in Amazon Kinesis Data Streams. Set the data stream as the origin for the distribution. Create an AWS Lambda function to consume and process data in the data stream.

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Questions 3

A solutions architect is designing an application to accept timesheet entries from employees on their mobile devices. Timesheets will be submitted weekly, with most of the submissions occurring on Friday. The data must be stored in a format that allows payroll administrators to run monthly reports The infrastructure must be highly available and scale to match the rate of incoming data and reporting requests.

Which combination of steps meets these requirements while minimizing operational overhead? (Select TWO}

Options:

A.  

Deploy the application to Amazon EC2 On-Demand Instances with load balancing across multiple Availability Zones. Use scheduled Amazon EC2 Auto Scaling to add capacity before the high volume of submissions on Fridays

B.  

Deploy the application in a container using Amazon Elastic Container Service (Amazon ECS) with load balancing across multiple Availability Zones Use scheduled Service Auto Scaling to add capacity before the high volume of submissions on Fridays

C.  

Deploy the application front end to an Amazon S3 bucket served by Amazon CloudFront Deploy the application backend using Amazon API Gateway with an AWSLambda proxy integration

D.  

Store the timesheet submission data in Amazon Redshift Use Amazon QuickSight to generate the reports using Amazon Redshift as the data source

E.  

Store the timesheet submission data in Amazon S3. Use Amazon Athena and Amazon QuickSight to generate the reports using Amazon S3 as the data source.

Discussion 0
Questions 4

A company wants to manage the costs associated with a group of 20 applications that are infrequently used, but are still business-critical, by migrating to AWS. The applications are a mix of Java and Node.js spread across different instance clusters. The company wants to minimize costs while standardizing by using a single deployment methodology.

Most of the applications are part of month-end processing routines with a small number of concurrent users, but they are occasionally run at other times Average application memory consumption is less than 1 GB. though some applications use as much as 2.5 GB of memory during peak processing. The most important application in the group is a billing report written in Java that accesses multiple data sources and often runs for several hours.

Which is the MOST cost-effective solution?

Options:

A.  

Deploy a separate AWS Lambda function tor each application. Use AWS CloudTrail logs and Amazon CloudWatch alarms to verify completion of critical jobs.

B.  

Deploy Amazon ECS containers on Amazon EC2 with Auto Scaling configured for memory utilization of 75%. Deploy an ECS task for each application being migrated with ECS task scaling. Monitor services and hosts by using Amazon CloudWatch.

C.  

Deploy AWS Elastic Beanstalk for each application with Auto Scaling to ensure that all requests have sufficient resources. Monitor each AWS Elastic Beanstalk deployment by using CloudWatch alarms.

D.  

Deploy a new Amazon EC2 instance cluster that co-hosts all applications by using EC2 Auto Scaling and Application Load Balancers. Scale cluster size based on a custom metric set on instance memory utilization. Purchase 3-year Reserved Instance reservations equal to the GroupMaxSize parameter of the Auto Scaling group.

Discussion 0
Questions 5

A company is planning to migrate its on-premises VMware cluster of 120 VMS to AWS. The VMS have many different operating systems and many custom software

packages installed. The company also has an on-premises NFS server that is 10 TB in size. The company has set up a 10 GbpsAWS Direct Connect connection to AWS for the migration

Which solution will complete the migration to AWS in the LEAST amount of time?

Options:

A.  

Export the on-premises VMS and copy them to an Amazon S3 bucket. Use VM Import/Export to create AMIS from the VM images that are stored in Amazon S3.Order an AWS Snowball Edge device. Copy the NFS server data to the device. Restore the NFS server data to an Amazon EC2 instance that has NFS configured.

B.  

Configure AWS Application Migration Service with a connection to the VMware cluster. Create a replication job for the VMS. Create an Amazon Elastic File System (Amazon EFS) file system. Configure AWS DataSync to copy the NFS server data to the EFS file system over the Direct Connect connection.

C.  

Recreate the VMS on AWS as Amazon EC2 instances. Install all the required software packages. Create an Amazon FSx for Lustre file system. Configure AWS DataSync to copy the NFS server data to the FSx for Lustre file system over the Direct Connect connection.

D.  

Order two AWS Snowball Edge devices. Copy the VMS and the NFS server data to the devices. Run VM Import/Export after the data from the devices isloaded to an Amazon S3 bucket. Create an Amazon Elastic File System (Amazon EFS) file system. Copy the NFS server data from Amazon S3 to the EFS file system.

Discussion 0
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