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In this video, we'll be learning how to make our file storage production-ready by moving uploaded images from local disk into AWS S3. We'll walk through creating an S3 bucket, configuring the bucket policy and IAM permissions, and integrating boto3 into our FastAPI application. We'll also refactor our image processing to separate it from the storage layer and handle boto3's blocking calls properly in our async app. By the end of the video, you'll have a production-ready file storage setup that can scale beyond a single server. Let's get started... The code from this video can be found here: https://github.com/CoreyMSchafer/FastAPI-16-AWS-S3-Image-Uploads Full FastAPI Course: https://www.youtube.com/playlist?list=PL-osiE80TeTsak-c-QsVeg0YYG_0TeyXI ✅ Support My Channel Through Patreon: https://www.patreon.com/coreyms ✅ Become a Channel Member: https://www.youtube.com/channel/UCCezIgC97PvUuR4_gbFUs5g/join ✅ One-Time Contribution Through PayPal: https://goo.gl/649HFY ✅ Cryptocurrency Donations: Bitcoin Wallet - 3MPH8oY2EAgbLVy7RBMinwcBntggi7qeG3 Ethereum Wallet - 0x151649418616068fB46C3598083817101d3bCD33 Litecoin Wallet - MPvEBY5fxGkmPQgocfJbxP6EmTo5UUXMot ✅ Corey's Public Amazon Wishlist http://a.co/inIyro1 ✅ Equipment I Use and Books I Recommend: https://www.amazon.com/shop/coreyschafer ▶️ You Can Find Me On: My Website - http://coreyms.com/ My Second Channel - https://www.youtube.com/c/coreymschafer Facebook - https://www.facebook.com/CoreyMSchafer Twitter - https://twitter.com/CoreyMSchafer Instagram - https://www.instagram.com/coreymschafer/ #Python #FastAPI