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Amazon AWS Certified Solutions Architect - Professional (SAP-C02) Sample Questions (Q412-Q417):
NEW QUESTION # 412
A solutions architect is designing the data storage and retrieval architecture for a new application that a company will be launching soon. The application is designed to ingest millions of small records per minute from devices all around the world. Each record is less than 4 KB in size and needs to be stored in a durable location where it can be retrieved with low latency. The data is ephemeral and the company is required to store the data for 120 days only, after which the data can be deleted.
The solutions architect calculates that, during the course of a year, the storage requirements would be about 10-15 TB.
Which storage strategy is the MOST cost-effective and meets the design requirements?
- A. Design the application to store each incoming record in an Amazon DynamoDB table properly configured for the scale. Configure the DynamoOB Time to Live (TTL) feature to delete records older than 120 days.
- B. Design the application to store each incoming record as a single .csv file in an Amazon S3 bucket to allow for indexed retrieval. Configure a lifecycle policy to delete data older than 120 days.
- C. Design the application to batch incoming records before writing them to an Amazon S3 bucket. Update the metadata for the object to contain the list of records in the batch and use the Amazon S3 metadata search feature to retrieve the data. Configure a lifecycle policy to delete the data after 120 days.
- D. Design the application to store each incoming record in a single table in an Amazon RDS MySQL database. Run a nightly cron job that executes a query to delete any records older than 120 days.
Answer: A
NEW QUESTION # 413
A company has an internal application running on AWS that is used to track and process shipments in the company's warehouse. Currently, after the system receives an order, it emails the staff the information needed to ship a package. Once the package is shipped, the staff replies to the email and the order is marked as shipped.
The company wants to stop using email in the application and move to a serverless application model.
Which architecture solution meets these requirements?
- A. Store new order information in Amazon EFS. Have instances pull the new information from the NFS and send that information to printers in the warehouse. Once the label has been scanned, as it leaves the warehouse, have Amazon API Gateway call the instances to remove the order information from Amazon EFS.
- B. Use AWS Batch to configure the different tasks required lo ship a package. Have AWS Batch trigger an AWS Lambda function that creates and prints a shipping label. Once that label is scanned. as it leaves the warehouse, have another Lambda function move the process to the next step in the AWS Batch job.B.
- C. Update the application to store new order information in Amazon DynamoDB. When a new order is created, trigger an AWS Step Functions workflow, mark the orders as "in progress," and print a package label to the warehouse. Once the label has been scanned and fulfilled, the application will trigger an AWS Lambda function that will mark the order as shipped and complete the workflow.
- D. When a new order is created, store the order information in Amazon SQS. Have AWS Lambda check the queue every 5 minutes and process any needed work. When an order needs to be shipped, have Lambda print the label in the warehouse. Once the label has been scanned, as it leaves the warehouse, have an Amazon EC2 instance update Amazon SOS.
Answer: C
NEW QUESTION # 414
A company has an application that uses Amazon EC2 instances in an Auto Scaling group. The quality assurance (QA) department needs to launch a large number of short-lived environments to test the application.
The application environments are currently launched by the manager of the department using an AWS CloudFormation template To launch the stack, the manager uses a role with permission to use CloudFormation EC2. and Auto Scaling APIs. The manager wants to allow testers to launch their own environments, but does not want to grant broad permissions to each user Which set up would achieve these goals?
- A. Upload the AWS CloudFormation template to Amazon S3 Give users in the QA department permission to use CloudFormation and S3 APIs, with conditions that restrict the permissions to the template and the resources it creates Train users to launch the template from the CloudFormation console.
- B. Create an AWS Service Catalog product from the environment template Add a launch constraint to the product with the existing role Give users in the QA department permission to use AWS Service Catalog APIs only_ Train users to launch the template from the AWS Service Catalog console.
- C. Create an AWS Elastic Beanstalk application from the environment template Give users in the QA department permission to use Elastic Beanstalk permissions only Train users to launch Elastic Beanstalk environments with the Elastic Beanstalk CLI, passing the existing role to the environment as a service role
- D. Upload the AWS CloudFormation template to Amazon S3. Give users in the QA department permission to assume the manager's role and add a policy that restricts the permissions to the template and the resources it creates Train users to launch the template from the CloudFormation console
Answer: B
NEW QUESTION # 415
A company needs to gather data from an experiment in a remote location that does not have internet connectivity. During the experiment, sensors that are connected to a total network will generate 6 TB of data in a preprimary formal over the course of 1 week. The sensors can be configured to upload their data files to an FTP server periodically, but the sensors do not have their own FTP server. The sensors also do not support other protocols. The company needs to collect the data centrally and move lie data to object storage in the AWS Cloud as soon. as possible after the experiment.
Which solution will meet these requirements?
- A. Order an AWS Snowball Edge Compute Optimized device. Connect the device to the local network.
Configure AWS DataSync with a target bucket name, and unload the data over NFS to the device. After the experiment return the device to AWS so that the data can be loaded into Amazon S3. - B. Order an AWS Snowcone device, including an Amazon Linux 2 AMI. Connect the device to the local network. Launch an Amazon EC2 instance on the device. Install and configure an FTP server on the EC2 instance. Configure the sensors to upload data to the EC2 instance. After the experiment, return the device to AWS so that the data can be loaded into Amazon S3.
- C. Order an AWS Snowcone device, including an Amazon Linux 2 AMI. Connect the device to the local network. Launch an Amazon EC2 instance on the device. Create a shell script that periodically downloads data from each sensor. After the experiment, return the device to AWS so that the data can be loaded as an Amazon Elastic Block Store [Amazon EBS) volume.
- D. Order an AWS Snowcone device. Connect the device to the local network. Configure the device to use Amazon FSx. Configure the sensors to upload data to the device. Configure AWS DataSync on the device to synchronize the uploaded data with an Amazon S3 bucket Return the device to AWS so that the data can be loaded as an Amazon Elastic Block Store (Amazon EBS) volume.
Answer: B
Explanation:
For collecting data from remote sensors without internet connectivity, using an AWS Snowcone device with an Amazon EC2 instance running an FTP server presents a practical solution. This setup allows the sensors to upload data to the EC2 instance via FTP, and after the experiment, the Snowcone device can be returned to AWS for data ingestion into Amazon S3. This approach minimizes operational complexity and ensures efficient data transfer to AWS for further processing or storage.
References: AWS Documentation on AWS Snowcone and Amazon EC2 provides detailed guidance on deploying compute and storage capabilities in edge locations. This solution leverages AWS's edge computing devices to address challenges associated with data collection in remote or disconnected environments.
NEW QUESTION # 416
A solutions architect needs to advise a company on how to migrate its on-premises data processing application to the AWS Cloud. Currently, users upload input files through a web portal.
The web server then stores the uploaded files on NAS and messages the processing server over a message queue. Each media file can take up to 1 hour to process. The company has determined that the number of media files awaiting processing is significantly higher during business hours, with the number of files rapidly declining after business hours.
What is the MOST cost-effective migration recommendation?
- A. Create a queue using Amazon MQ.
Configure the existing web server to publish to the new queue.
When there are messages in the queue, create a new Amazon EC2 instance to pull requests from the queue and process the files.
Store the processed files in Amazon EFS. Shut down the EC2 instance after the task is complete. - B. Create a queue using Amazon SQS.
Configure the existing web server to publish to the new queue.
Use Amazon EC2 instances in an EC2 Auto Seating group to pull requests from the queue and process the files.
Scale the EC2 instances based on the SQS queue length. Store the processed files in an Amazon S3 bucket. - C. Create a queue using Amazon MQ.
Configure the existing web server to publish to the new queue.
When there are messages in the queue, invoke an AWS Lambda function to pull requests from the queue and process the files.
Store the processed files in Amazon EFS. - D. Create a queue using Amazon SQS.
Configure the existing web server to publish to the new queue.
When there are messages in the queue, invoke an AWS Lambda function to pull requests from the queue and process the files.
Store the processed files in an Amazon S3 bucket.
Answer: B
Explanation:
As the length of processing the files take 1 hour, Lambda seems to be out of question, then we are left with EC2 option D seems to be correct as we are auto-scaling EC2.
https://aws.amazon.com/blogs/compute/operating-lambda-performance-optimization-part-1/
NEW QUESTION # 417
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