FastAPI Implementation Using AWS Lambda

A Guide to Deploying Machine Learning Models Using AWS Lambda Function from Container Images

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Welcome to the FastAPI using AWS Lambda project! This project showcases the integration of FastAPI, a web framework for building APIs with Python, with AWS Lambda using containerization of our app.

Project's Goal

To demonstrate how to integrate and deploy a machine learning model as an api within a Docker container, utilizing the capabilities of AWS Lambda and Amazon ECR for container image deployment.

In this project,

• I've built an API using FastAPI [app.py] which uses a machine learning model for classification using the model's pickle file.
• Then I've encapsulated this API within a Docker container and deployed the container using Amazon Elastic Container Registry(ECR) .
• Then create a Lambda function from the container image and adding Amazon API Gateway as a trigger.

Follow this step-by-step guide to:

• Set up the environment
• Build the Docker container image
• Deploy it to AWS ECR
• Create an AWS Lambda function
• Link it to an API Gateway trigger

Prerequisites

• Python (>3.8)
• AWS account
• Docker