Exam AWS Certified Solutions Architect - Professional SAP-C02 topic 1 question 18 discussion

This solution meets the requirements by using multiple managed services offered by AWS which can reduce the operational overhead. Hosting the web application in Amazon S3 would make it highly available, scalable and can handle variable traffic. The uploaded videos can be stored in S3 and processed using S3 event notifications that trigger a Lambda function, which calls the Amazon Rekognition API to categorize the videos. SQS can be used to process the event notifications and also it is a managed service. This solution eliminates the need to manage EC2 instances, EBS volumes and the custom software. Additionally, using Lambda function in this case, eliminates the need for managing additional servers to process the SQS queue which will reduce operational overhead. By using this solution, the company can benefit from the scalability, reliability, and cost-effectiveness that these services offer, which can help to reduce operational overhead and improve the overall performance and security of the application.

D. Because, you cannot host web application in S3, only static web assets. ElasticBeanStalk provides an easy way to onboard autoscaling web apps with minimal operational overheads.

Answer A doesn't really address the operational burden, and the Spot instance stuff is a distractor. Answer C (hosting the static website in S3, along with the videos, and switching to Rekognition with S3 events) provides the most reduction in operational burden, and as a plus is also going to be the lowest-cost solution.

The Amazon Rekognition Video API facilitates the analysis of videos either stored in an Amazon S3 bucket or streamed via Amazon Kinesis Video Streams. https://docs.aws.amazon.com/rekognition/latest/dg/how-it-works-operations-intro.html

'static website' = Amazon S3 'store videos'= Amazon S3 'video analysis' = Amazon Rekognition 'reduce operational overhead, managed service' = S3 events, AWS Lambda, Amazon SQS

The answer is C. This solution eliminates the need for managing and scaling EC2 instances for the web application and the worker environment for processing the SQS queue. Instead, Amazon S3 can host the web application, and store the uploaded videos, which can trigger S3 event notifications to send messages to the SQS queue. Then, an AWS Lambda function can process the messages in the SQS queue and use Amazon Rekognition API to categorize the videos. This approach also takes advantage of AWS-managed services, such as S3, SQS, and Lambda, which reduces operational overhead and dependency on third-party software.

C. Host the web application in Amazon S3. Store the uploaded videos in Amazon S3. Use S3 event notification to publish events to the SQS queue. Process the SQS queue with an AWS Lambda function that calls the Amazon Rekognition API to categorize the videos. Explanation: Hosting the Web Application in Amazon S3: Cost-effective and Scalable: Amazon S3 is a cost-effective and scalable solution for hosting static web content. It can handle variable traffic efficiently without the need to manage servers. Static Content Hosting: Ideal for serving static content like HTML, CSS, JavaScript, and media files.

While I vote for C, I do think however that whether we can go with C really depends on the application codebase. The use case mentions that the application enables file uploads. We know that handling files require a backend, if your application is written in something like Java. If that's the case, you won't be able to host your application in S3. The phrase "website contains static content" is really vague, as it does not reveal anything about the backend of the application. Now, the fact that the application has EBS to store Video files give up a hint, that suggests that the application has some BE code. I am taking a hint from "re-architect" I assume involves some revamping of the applications codebase. So, here's how I'd go about "re-architecting" 1. Move storage of files to S3. 2. Eliminate the BE codebase, revamp the FE codebase to rely entirely on AWS JS SDK and handle file uploads with that. Now you don't need to manage any compute resources at all. 3. Go about the rest of the solution.

The mention of static content really throws this question off and clearly the community thinks this as well. The argument of static website vs static content being the key to selecting D isn't really a strong argument but that doesn't exclude D from being a viable solution. Operational overhead is minimized with Elastic Beanstalk and removes dependencies on third party tools/software.

If it were D - how would Rekognition access the videos to classify? Rekognition would need to ssh into the EBS volume of various beanstalk instances running under an ASG (impossible as far as I know). I agree though - I think the wording is terrible for 'contains static content'; as how on earth would this type of app practically run on s3 alone for login/ user auth etc.. would need to be coupled with other serverless products such as lambda/cognito etc.

C. Host the web application in Amazon S3. Store the uploaded videos in Amazon S3. Use S3 event notification to publish events to the SQS queue. Process the SQS queue with an AWS Lambda function that calls the Amazon Rekognition API to categorize the videos.

I saw this question in other question bank (owner of the questions) and it is A, reason is assuming is moving files back and forth cannot be static page, so it is A.

Only Answer C is the solution that covers all the requirements, where the videos are stored, how SQS messages are produced and consumed, how web app is hosted.

C, this is a typical scenario

re-architect the application to reduce operational overhead

Elastic bean stack is not required , it is a static content only, better can go with S3. So Answer is C

C videos in Amazon S3