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Answer: Save the .pdf files to Amazon S3. Configure an S3 PUT event to invoke an AWS Lambda function to convert the files to .jpg format and store them back in Amazon S3.
## Explanation **Option A is the most cost-effective solution** because: 1. **Serverless Architecture**: Using S3 with Lambda provides a serverless, pay-per-use model where you only pay for the compute time used during PDF conversion and storage used. 2. **Scalability**: S3 automatically scales to handle any number of files, and Lambda can scale to thousands of concurrent executions to handle rapid growth. 3. **Cost Efficiency**: - No EC2 instances to provision or manage - No idle compute costs (Lambda only runs when files are uploaded) - S3 storage is highly cost-effective for large files - No EBS or EFS storage costs 4. **Event-Driven Processing**: The S3 PUT event triggers Lambda automatically, creating a seamless workflow. 5. **Storage Optimization**: Both original PDFs and converted JPGs can be stored in S3 with appropriate lifecycle policies. **Why other options are less cost-effective**: - **Option B (DynamoDB)**: DynamoDB is a NoSQL database optimized for key-value access, not for storing large binary files. It would be extremely expensive to store 5MB files in DynamoDB compared to S3. - **Option C (Elastic Beanstalk with EBS)**: Requires provisioning and managing EC2 instances, which means paying for compute capacity even during idle periods. EBS storage is more expensive than S3 for this use case, and scaling requires managing Auto Scaling groups. - **Option D (Elastic Beanstalk with EFS)**: Similar to Option C but with EFS, which is a shared file system. While EFS allows multiple EC2 instances to access the same files, it's more expensive than S3 and still requires EC2 instances to be running. **Key AWS Services Used**: - **Amazon S3**: For cost-effective, scalable object storage - **AWS Lambda**: For serverless, event-driven compute - **S3 Event Notifications**: To trigger processing automatically This solution aligns with AWS best practices for cost optimization by leveraging serverless services that scale automatically and only incur costs when actually processing files.
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A company runs its infrastructure on AWS and has a registered base of 700,000 users for its document management application. The company intends to create a product that converts large .pdf files to .jpg image files. The .pdf files average 5 MB in size. The company needs to store the original files and the converted files. A solutions architect must design a scalable solution to accommodate demand that will grow rapidly over time.
Which solution meets these requirements MOST cost-effectively?
A
Save the .pdf files to Amazon S3. Configure an S3 PUT event to invoke an AWS Lambda function to convert the files to .jpg format and store them back in Amazon S3.
B
Save the .pdf files to Amazon DynamoDB using the DynamoDB Streams feature to invoke an AWS Lambda function to convert the files to .jpg format and store them back in DynamoDB.
C
Upload the .pdf files to an AWS Elastic Beanstalk application that includes Amazon EC2 instances, Amazon Elastic Block Store (Amazon EBS) storage, and an Auto Scaling group. Use a program in the EC2 instances to convert the files to .jpg format. Save the .pdf files and the .jpg files in the EBS store.
D
Upload the .pdf files to an AWS Elastic Beanstalk application that includes Amazon EC2 instances, Amazon Elastic File System (Amazon EFS) storage, and an Auto Scaling group. Use a program in the EC2 instances to convert the file to .jpg format. Save the .pdf files and the .jpg files in the EBS store.
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