Download Latest SAP-C02 Questions

AWS Certified Solutions Architect - Professional Questions and Answers

Question 17

A company is migrating a document processing workload to AWS. Client applications upload documents to an Amazon S3 bucket for processing. A document processing engine runs on an Amazon EC2 Linux instance and requires Portable Operating System Interface (POSIX)-compliant file system access to read, generate, and modify files during processing. The processed documents must be automatically available in the S3 bucket for client applications to download.

The company cannot directly modify the document processing engine to use the S3 API. The company needs a solution that provides the EC2 instance with file system access. The solution must maintain automatic synchronization with the S3 bucket for both input and output files.

Which solution will meet these requirements?

Options:

Configure AWS DataSync to connect to the EC2 instance without an agent. Configure a DataSync task in enhanced mode to synchronize the processed documents to and from Amazon S3.

Configure an Amazon FSx for Lustre file system with import and export policies that are linked to the S3 bucket. Install the Lustre client on the EC2 instance and mount the file system.

Create an Amazon EFS file system. Set the data repository associations to the S3 bucket. Install the EFS client and mount the file system. Create an automatic import and export policy for new and changed objects.

Set up an Amazon S3 File Gateway. Initiate a RefreshCache API call to update the S3 File Gateway when changes occur in Amazon S3.

Answer:

Explanation:

B is correct because Amazon FSx for Lustre provides a high-performance, POSIX-compliant file system that can be directly linked with Amazon S3 using data repository integration. This allows the EC2-based processing engine (which requires POSIX file operations) to read/write files through a mounted Lustre file system while automatically importing objects from S3 and exporting results back to S3 using Lustre’s S3 integration policies. This satisfies all requirements: POSIX file access, no need to change the application to use the S3 API, and automated synchronization for both inputs and outputs.

Why the other options are incorrect:

A: DataSync is designed for scheduled or task-based data transfers. It does not provide a mounted POSIX file system interface for the application to read/write “in place,” and the “without an agent” requirement is not a fit for an EC2-hosted POSIX workflow that needs continuous file semantics.

C: Amazon EFS is POSIX and mountable, but “data repository associations to S3” is not an EFS capability in the way described. EFS does not provide native bidirectional automatic sync with S3 using import/export policies like FSx for Lustre’s S3 integration.

D: S3 File Gateway provides a file interface backed by S3, but keeping cache coherent with explicit RefreshCache calls is operationally complex and not truly “automatic synchronization” in the sense required. It also introduces caching behaviors that can complicate immediate availability expectations.

[References:, Amazon FSx for Lustre Documentation: POSIX-compliant Lustre file system; data repository integration with S3; import/export behavior and policies, Amazon S3 Documentation: object storage model and integration patterns with file systems, AWS Storage Gateway Documentation: S3 File Gateway behavior, caching, and RefreshCache operations, AWS Certified Solutions Architect – Professional (SAP-C02) Exam Guide: selecting storage services for migration constraints (POSIX needs, minimal refactoring, S3 integration), , , ]

Question 18

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?

Options:

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.

Create a queue using Amazon M. 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.

Create a queue using Amazon MO. 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.

Create a queue using Amazon SOS. Configure the existing web server to publish to the new queue. Use Amazon EC2 instances in an EC2 Auto Scaling group to pull requests from the queue and process the files. Scale the EC2 instances based on the SOS queue length. Store the processed files in an Amazon S3 bucket.

Question 19

A company hosts a game player-matching service on a public-facing, physical, on-premises instance that all users are able to access over the instance uses UDP. The company wants to migrate the service to AWS and provide a high level of security. A solutions architect needs to de matching service using AWS.

Which combination of steps should the solutions architect take to meet these requirements? (Select THREE.)

Options:

Use a Network Load Balancer (NLB) in front of the player-matching instance. Use a friendly DNS entry in Amazon Route 53-point address.

Use an Application Load Balancer (ALB) in front of the player-matching instance. Use a friendly DNS entry in Amazon Route 53 p facing fully qualified domain name (FQDN).

Define an AWS WAF rule to explicitly drop non-UDP traffic, and associate the rule with the load balancer.

Configure a network ACL rule to block all non-UDP traffic. Associate the network ACL with the subnets that hold the load balance

Question 20

A financial services company receives a regular data feed from its credit card servicing partner Approximately 5.000 records are sent every 15 minutes in plaintext, delivered over HTTPS directly into an Amazon S3 bucket with server-side encryption. This feed contains sensitive credit card primary account number (PAN) data The company needs to automatically mask the PAN before sending the data to another S3 bucket for additional internal processing. The company also needs to remove and merge specific fields, and then transform the record into JSON format Additionally, extra feeds are likely to be added in the future, so any design needs to be easily expandable.

Which solutions will meet these requirements?

Options:

Trigger an AWS Lambda function on file delivery that extracts each record and writes it to an Amazon SQS queue. Trigger another Lambda function when new messages arrive in the SQS queue to process the records, writing the results to a temporary location in Amazon S3. Trigger a final Lambda function once the SQS queue is empty to transform the records into JSON format and send the results to another S3 bucket for internal processing.

Trigger an AWS Lambda function on file delivery that extracts each record and writes it to an Amazon SQS queue. Configure an AWS Fargate container application to automatically scale to a single instance when the SQS queue contains messages. Have the application process each record, and transform the record into JSON format. When the queue is empty, send the results to another S3bucket for internal processing and scale down the AWS Fargate i

Create an AWS Glue crawler and custom classifier based on the data feed formats and build a table definition to match. Trigger an AWS Lambda function on file delivery to start an AWS Glue ETL job to transform the entire record according to the processing and transformation requirements. Define the output format as JSON. Once complete, have the ETL job send the results to another S3 bucket for internal processing.

Create an AWS Glue crawler and custom classifier based upon the data feed formats and build a table definition to match. Perform an Amazon Athena query on file delivery to start an Amazon EMR ETL job to transform the entire record according to the processing and transformation requirements. Define the output format as JSON. Once complete, send the results to another S3 bucket for internal processing and scale down the EMR cluster.

Summer Certification Sale 70% Discount Offer - Ends in 0d 00h 00m 00s - Coupon code: save70

AWS Certified Solutions Architect - Professional Questions and Answers

Options:

Answer:

Explanation:

Options:

Answer:

Explanation:

Options:

Answer:

Options:

Answer:

Explanation:

CompTIA

Fortinet

Microsoft

Salesforce