A company has an application that customers use to upload images to an Amazon S3 bucket. Each night, the company launches an Amazon EC2 Spot Fleet that processes all the images that the company received that day. The processing for each image takes 2 minutes and requires 512 MB of memory.
A solutions architect needs to change the application to process the images when the images are uploaded.
Which change will meet these requirements MOST cost-effectively?
Using S3 Event Notifications to trigger a message to an Amazon Simple Queue Service (Amazon SQS) queue and then configuring an AWS Lambda function to read the messages from the queue and process the images meets the requirements most cost-effectively. AWS Lambda is designed to handle short-lived tasks and can easily scale to handle the varying load of image uploads without the need for provisioning or managing servers. Given that each image processing task takes 2 minutes and requires 512 MB of memory, these requirements fall well within Lambda's capabilities.
Answer A I would go with Lambda and SQS. when using SQS we will be sure that all images will be processed and hence to process we need 2 min and 512 MB of memory (Lambda is allowing upto 15 min and upto10K MB) Lambda should be perfect scalable solution which will allow for almost in real time image processing.
and it is cost effective ;)
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less than 5 minutes -> use lambda
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(B) is eliminated. Reserved instances are more expensive than Spot Fleet. (C) is eliminated. Container instance more expensive than Lambda. SQS needed NOT SNS. (D) is eliminated. Elastic Beanstalk is more expensive than Spot Fleet. SQS needed NOT SNS. (A) is correct. It's the most cost effective service & the scope of its capabilities are within the requirements.
A. Use S3 Event Notifications to write a message with image details to an Amazon Simple Queue Service (Amazon SQS) queue. Configure an AWS Lambda function to read the messages from the queue and to process the images.