Wrong Answer flagged as correct?

[kardangs009]

A media company recently launched a web service that allows users to upload and share short videos. Currently, the web servers are hosted on an Auto Scaling group of Amazon EC2 instances in which the videos are processed and stored in the EBS volumes. Each uploaded video sends a message on the Amazon SQS queue, which is also processed by an Auto Scaling group of Amazon EC2 instances. The company relies on third-party software to analyze and categorize the videos. The website also contains static content that has variable user traffic. The company wants to re-architecture the application to reduce costs, reduce dependency on third-party software, and reduce management overhead by leveraging AWS-managed services.

Which of the following solutions will meet the company’s requirements?

A. Create an Amazon S3 bucket with website hosting enabled to host the web application. Store the videos and static content on a separate S3 bucket. Configure S3 event notification to send messages to an Amazon SQS queue for each video upload event. Have AWS Lambda poll the Amazon SQS queue for messages and invoke a Lambda function that calls the Amazon Rekognition API to analyze and categorize the videos.

B. Reduce operational overhead by using AWS Elastic Beanstalk to provision the Auto Scaling group of EC2 instances for the web servers and the Amazon SQS queue consumers. Use Amazon Rekognition to analyze and categorize the videos instead of the third-party software. Store the videos and static contents on Amazon S3 buckets.

C. Create an Amazon ECS Fargate cluster and use containers to host the web application. Create an Auto Scaling group of Amazon EC2 Spot instances to process the SQS queue. Use Amazon Rekognition to analyze and categorize the videos instead of the third-party software. Store the videos and static contents on Amazon S3 buckets.

D. Create an Amazon EFS volume to store the videos and static content. Mount the volume on all EC2 instances of the web application. Have AWS Lambda poll the Amazon SQS queue for messages and invoke a Lambda function that calls the Amazon Rekognition API to analyze and categorize the videos

The correct answer is shown as option C. However the question clearly states reduce management overhead and cost, so using beanstalk to depoly reduces management overhead compared to Fargate right? ALso costwise its more effective? Please clarify

[kardangs009]

Just to add, i tried checking the same with chatgpt, it suggests S3 bucket to be used as website (Option A) as the right answer. This needs some more understanding or clarification i guess

• This reply was modified 3 weeks, 2 days ago by  kardangs009.

[JR-TutorialsDojo]

Hello kardangs009,

Thank you for reaching out.

The correct option leverages Spot Instances to process the SQS queue, which makes background video processing more cost‑effective since Spot pricing is significantly lower than On‑Demand. When combined with Fargate’s pay‑as‑you‑use model, this approach reduces both costs and operational burden more effectively than Elastic Beanstalk.

While Beanstalk does simplify EC2 management, it still runs on EC2 under the hood and does not mention Spot Instances for queue processing, which means it misses out on additional cost savings.

As for the suggestion about S3 website hosting, that works well for static sites, but this scenario involves dynamic video uploads and processing. Because of that, S3 hosting alone isn’t sufficient.

I suggest carefully reviewing the explanation provided and identifying any unclear parts so we can address the specific areas of confusion.

Regards,
JR @ Tutorials Dojo