AI Project Deployment End-to-End | Docker + EC2 + FastAPI Production Deployment

Description

In this video, we understand how real-world AI and GenAI applications are deployed in production using FastAPI, Docker, DockerHub, and AWS EC2. We cover the complete deployment lifecycle starting from notebook experimentation to Docker container deployment on cloud virtual machines. This session is extremely useful for: AI Interviews GenAI Deployment FastAPI Backend Projects Docker Deployment AWS EC2 Deployment Production AI Systems 🔗 Reference GitHub Repo https://github.com/switch2ai 🧠 AI Project Workflow Experimentation performed in notebook files .ipynb used for research and testing Production Conversion Notebook logic converted into Python scripts .py files used for APIs and production applications ⚙️ Complete Development Lifecycle Experimentation Python Script/API Local Testing Dockerization Push to DockerHub Deploy on EC2 Run Docker Container Production Access 🏗️ Backend Project Structure app/ api/ services/ config/ model/ core/ utils/ main.py requirements.txt Dockerfile 📂 Folder Explanation api Contains endpoints and API routes Handles incoming client requests services Contains actual business logic RAG pipelines LLM workflows AI processing config Stores configuration files Secrets Constants Environment settings core Reusable functions shared across multiple services utils Helper utility functions Common reusable methods model Contains Pydantic schemas Request and response validation main.py Application entry point FastAPI initialization rag.py Contains RAG implementation logic Retriever Embedding LLM interactions 🌍 Environment Management Production applications generally maintain multiple environments Dev Test Prod 🔐 Environment Variables .env file used for storing sensitive information securely Example OPENAI_API_KEY ⚙️ python-dotenv Used for loading environment variables inside Python applications Helps avoid hardcoding secrets 🚀 Deployment Pipeline Experimentation in notebooks Convert notebook logic into Python APIs Test application locally Create Dockerfile Build Docker image Run Docker container locally Push image to DockerHub Launch EC2 server Pull image inside EC2 Run container in production 🐳 Docker Workflow Dockerfile contains instructions to build application Docker Image packages application and dependencies Docker Container runs application from image ⚙️ Build Docker Image docker build command creates image from Dockerfile Image tested locally before deployment ▶️ Run Docker Container docker run command starts container from image Detached mode runs container in background Port mapping exposes container application to outside world Environment variables passed using .env file 🌐 Port Mapping 8000:8000 Host port mapped to container port Allows external access to FastAPI application ☁️ DockerHub Workflow Tag local image Push image to DockerHub repository Pull image from cloud server 🖥️ AWS EC2 Deployment Launch EC2 instance Connect using SSH and .pem key Install Docker on EC2 Pull Docker image from DockerHub Run container on server 🔐 Security Groups Inbound Rules Control who can access server Outbound Rules Control outgoing traffic from server 🌍 Access Application FastAPI Swagger Docs accessible using public-ip:8000/docs 🧠 Interview Discussion Points Always explain Project architecture Deployment workflow Environment handling Docker lifecycle Cloud deployment steps Security handling Production scalability ⚠️ Common Challenges Environment variable management Port conflicts Docker permission issues Dependency mismatch Container networking Cloud firewall/security group configuration 🚀 Key Takeaways Production AI applications require structured deployment pipelines Docker simplifies packaging and portability DockerHub helps image distribution EC2 used for scalable deployment Environment management is critical for security FastAPI widely used for GenAI backend APIs 🔥 Hashtags #Docker #FastAPI #AWS #EC2 #GenAI #AIProjects #MachineLearning #LLM #BackendDevelopment #Switch2AI 🔍 SEO Tags docker deployment tutorial fastapi deployment on ec2 genai project deployment dockerhub tutorial aws ec2 docker deployment ai backend deployment fastapi docker production python api deployment rag deployment architecture production ai application 🔍 SEO Tags (500 char) docker deployment tutorial,fastapi deployment on ec2,genai project deployment,dockerhub tutorial,aws ec2 docker deployment,ai backend deployment,fastapi docker production,python api deployment,rag deployment architecture,production ai application,docker container deployment,ec2 fastapi hosting,production genai backend,Switch 2 AI