<|im_start|>system
You are a helpful AI assistant.<|im_end|>
<|im_start|>user
What is the best design of a system that uploads a file to S3, than resizes it with lambda but using the same key as uploaded, without triggering the resize lambda function twice or more?<|im_end|>
<|im_start|>assistant
A possible solution to this problem is to use a S3 bucket event trigger to trigger the resizing Lambda function when a new file is uploaded to the S3 bucket. You can set the event to trigger the Lambda function only when a new object is created, not when it's modified. The Lambda function can then resize the file and store the resized version in the same S3 bucket using the same key as the original file, but with a different file format (e.g. adding "_resized" to the filename).

Additionally, you can add a check in the Lambda function to ensure it only resizes the file once. For example, you can store metadata in the object's metadata in S3 to indicate whether the file has been resized or not. Before resizing, the Lambda function can check this metadata and only resize the file if it hasn't been resized already.

By combining these two strategies, you can ensure that the Lambda function is triggered only once for each new file uploaded to the S3 bucket and that the resized version is stored in the same S3 bucket with the same key as the original file.<|im_end|>
<|im_start|>user
Show me how with AWS SAM CLI commands or as a bash script<|im_end|>
<|im_start|>assistant
Here's an example AWS SAM CLI command to create a SAM template for this setup:
sam init --runtime python3.8
cd sam-app/
sam build
sam package --output-template-file packaged.yaml
sam deploy --template-file packaged.yaml --stack-name s3-resize-stack --capabilities CAPABILITY_IAM

Here's the Sam template: 

---
AWSTemplateFormatVersion: '2010-09-09'
Transform: AWS::Serverless-2016-10-31
Resources:
  S3Bucket:
    Type: AWS::S3::Bucket
    DeletionPolicy: Retain
    Properties:
      BucketName: my-resize-bucket
      NotificationConfiguration:
        LambdaConfigurations:
          - Event: s3:ObjectCreated:*
            Function: !GetAtt LambdaResizeFunction.Arn

  LambdaResizeFunction:
    Type: AWS::Serverless::Function
    Properties:
      CodeUri: resize_function.py
      Handler: index.handler
      Runtime: python3.8
      Environment:
        Variables:
          S3_BUCKET: !Ref S3Bucket
      Policies:
        - S3CrudPolicy:
            BucketName: !Ref S3Bucket

And here's an example Python script for the Lambda function that resizes the uploaded file:

import boto3

def handler(event, context):
    s3 = boto3.client('s3')
    bucket_name = os.environ['S3_BUCKET']

    for record in event['Records']:
        file_key = record['s3']['object']['key']
        # resize the file using the boto3 library
        # save the resized file back to S3 with the same key
        s3.upload_file(resized_file, bucket_name, file_key)

This setup ensures that the Lambda function is triggered only once per new object uploaded and resizes the file using the same key.<|im_end|>
<|im_start|>user
Suggest an alternative approach that keeps the original filenames.<|im_end|>
<|im_start|>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.<|im_end|>