Ambiguious question

[Benny25]

Hello, I am referring to the following question:

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 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 requirements?

– 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.

– 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.

– 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.

– 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.

The correct answer is 1. The explanation for answer 3 is :

“There is no mention in the question
regarding the nature of the application but we can safely assume that
this website is a dynamic website that allows users to log in and upload
videos. We can’t safely host a dynamic website on an Amazon S3 bucket.”

I actually read the question multiple times because I was hesitant between the two answers for this exact reason. But as said, there is no mention of any treatment made by the EC2, only the storing. If you wanted to highlight that the EC2 does more than storing, just add something like:

“Currently, the web servers are hosted on an Auto Scaling group of
Amazon EC2 instances in which the videos are PROCESSED/FILTER/VERIFIED AND then stored in the EBS volumes.”

This removes any ambiguity.

[JR-TutorialsDojo]

Hi Benny25,

I understand how the mention of storing with regard to EC2 might have been a bit ambiguous. However, given that the web service allows users to upload and share videos, it inherently requires some dynamic operations, such as processing uploads, storing metadata about the videos, dynamically retrieving videos for viewers, etc. These elements suggest a dynamic nature of the service, even if not explicitly stated.

Having said that, we appreciate your attention to detail. Your suggestion to add a statement like “the videos are PROCESSED/FILTERED/VERIFIED AND then stored in the EBS volumes” would indeed make it clearer that server-side processing is required, thus eliminating any ambiguity. Thank you for your feedback!

Regards,
JR @ Tutorials Dojo