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Amazon SAP-C02 Exam - Topic 1 Question 53 Discussion

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?
D) 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.
A) 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.
B) 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.
C) 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.

Amazon SAP-C02 Exam - Topic 1 Question 53 Discussion

Actual exam question for Amazon's SAP-C02 exam
Question #: 53
Topic #: 1
[All SAP-C02 Questions]

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?

Show Suggested Answer Hide Answer
Suggested Answer: D

https://aws.amazon.com/blogs/compute/operating-lambda-performance-optimization-part-1/


by Terrilyn at Apr 05, 2025, 12:45 AM

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Tatum
6 months ago
Wait, can Lambda really handle that long processing time?
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Kris
6 months ago
Option D sounds complicated with EC2 scaling.
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Anastacia
6 months ago
I agree, Lambda is great for scaling!
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Bette
6 months ago
Not sure about using EFS in option C, isn't S3 cheaper?
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Alishia
6 months ago
Option A seems the most efficient with Lambda and S3.
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In
7 months ago
I feel like using an EC2 Auto Scaling group could be overkill for this scenario, especially if the workload fluctuates so much during business hours.
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Jerrod
7 months ago
I practiced a similar question where we had to decide between EC2 and Lambda, and I think Lambda might be better here since the processing time is long and variable.
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Carin
7 months ago
I'm not entirely sure, but I think using Amazon S3 for storage is generally more cost-effective than EFS, especially for large media files.
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Corrie
7 months ago
I remember discussing the benefits of using AWS Lambda for cost efficiency, especially since it only charges for the compute time used.
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Evette
7 months ago
Option A seems like a good starting point. Leveraging serverless services like SQS and Lambda should help optimize costs and scalability. I'll make sure to review the pricing and performance details for those services to validate the recommendation.
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Loren
8 months ago
The variable workload during business hours is an important consideration. I like the idea of using an auto-scaling group in option D to handle the fluctuations, but I'm not sure if that would be more cost-effective than the Lambda approach in option A.
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Alverta
8 months ago
I'm a bit confused by the different queue options - what are the key differences between SQS, MQ, and SOS? I'll need to review the AWS service details to understand which one would be the best fit here.
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Daryl
8 months ago
This seems like a straightforward migration scenario, and I think option A looks like the most cost-effective approach. Using Lambda to process the files on-demand should help manage the variable workload.
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Janae
1 year ago
Wow, 1 hour to process a media file? I wonder if they're using a potato as the processing server. Probably need to upgrade that hardware, ya think?
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Josefa
12 months ago
C: I agree, and storing the files in an S3 bucket is cost-effective too.
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Giuseppe
12 months ago
B: Yeah, Lambda can definitely help speed up the processing time.
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Hannah
12 months ago
A: A sounds like the best option. Using Lambda to process the files seems efficient.
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Latanya
1 year ago
C, really? MO? I think you meant to say SQS. That's a typo waiting to happen on the exam!
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Pedro
1 year ago
D looks tempting, but the cost of running EC2 instances 24/7 might be higher than the other options. Gotta keep an eye on that queue length.
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Casie
11 months ago
C) 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.
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Buck
11 months ago
A sounds like a good option. Using Lambda for processing can save costs compared to running EC2 instances all the time.
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Marylyn
1 year ago
B) 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.
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Veronique
1 year ago
A) 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.
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Wava
1 year ago
I'm not convinced that EFS is the best storage option here. S3 might be a better choice for its durability and scalability.
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Estrella
12 months ago
A: Definitely. Plus, using AWS Lambda to process the files can help with cost-effectiveness and scalability.
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Maddie
12 months ago
B: I agree. S3 is more durable and scalable compared to EFS. It's a better option for storing the processed files.
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Alberta
1 year ago
A: I think option A is the best choice. Using Amazon SQS and storing the processed files in an Amazon S3 bucket makes sense.
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Malcolm
1 year ago
I prefer option D. Using EC2 instances with Auto Scaling can handle high workload.
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Kip
1 year ago
I agree with Lizbeth. Using Amazon SQS and AWS Lambda seems efficient.
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Lashandra
1 year ago
A seems like the most cost-effective option. Lambda functions are a great way to handle the variable workload without the need to manage EC2 instances.
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Anglea
12 months ago
User 3: Lambda functions are great for handling variable workloads efficiently, especially when the number of files to process fluctuates throughout the day.
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Xochitl
12 months ago
User 2: Definitely, using Lambda functions to process the files based on the queue messages is a smart move.
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Lyla
12 months ago
User 1: I agree, option A with Lambda functions seems like the best choice for cost-effectiveness.
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Lizbeth
1 year ago
I think option A is the most cost-effective recommendation.
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