assistant: A possible design for this system would be to use a combination of Amazon S3 and AWS Lambda with a DynamoDB table to store metadata and prevent duplicates. Here's a high-level overview of the process:

1. User uploads a file to a designated S3 bucket, where it is stored with its original filename as the key.
2. S3 bucket triggers a Lambda function upon receiving a new file. The Lambda function checks if the file has already been processed by looking up its filename in a DynamoDB table.
3. If the file is not found in the DynamoDB table, the Lambda function reads the file from S3, resizes it, and writes the resized file back to S3 with the same key (filename) as the original file. The Lambda function then adds an entry for the file in the DynamoDB table.
4. If the file is found in the DynamoDB table, the Lambda function does not perform any resizing and exits.

This approach uses the filename as the key for both the original file and the resized file in S3, ensuring that the original filenames are preserved. The DynamoDB table serves as a deduplication mechanism to prevent the same file from being resized multiple times. The Lambda function is triggered only once per file and will only resize a file if it has not been processed before.

assistant: An alternative approach that keeps the original filenames could be:

Upload file to S3 as before
S3 triggers Lambda
Lambda checks if file has already been resized by looking for an ".resized" tag on the S3 object
If tag exists, Lambda exits
If tag does not exist:

Lambda resizes the image
Lambda copies the resized image to a new S3 object with the same key (filename)
Lambda adds ".resized" tag to original S3 object

This approach stores the resized file with the same filename, and uses object tags to keep track of which files have been resized.

prompter: How to check if file has a ".resized" tag?

assistant: A possible solution to this problem is to use Amazon S3's object metadata and AWS Step Functions to coordinate the file upload and image resizing process. Here's a high-level overview of the system design:

File upload: When a user uploads a file to the S3 bucket, a metadata entry is added to the object that includes a flag indicating that the file has not been processed.

Step Function: The Step Function is triggered by a S3 bucket object creation event, and it contains two states: a Wait state and a Lambda function state.

Wait state: In this state, the Step Function waits for a specified period of time (e.g., 5 minutes) to ensure that the S3 object has finished uploading and is fully available.

Lambda function state: The Lambda function state is responsible for checking the metadata flag on the S3 object. If the flag indicates that the file has not been processed, the Lambda function resizes the file and updates the metadata flag to indicate that the file has been processed. If the flag indicates that the file has already been processed, the Lambda function exits without doing anything.

By using the Step Function's Wait state and S3 object metadata, this system ensures that the Lambda function is only triggered once and that the original file names are preserved.

Note: This is just a high-level overview and further details, such as error handling, may need to be added to the design to ensure a fully functioning system.