AI Image Generation Service using Amazon Bedrock & Stable Diffusion
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Project Overview
This AI image generation service leverages Amazon Bedrock’s Stable Diffusion model to generate high-quality images based on user prompts, using a scalable cloud architecture built on AWS. The project covers infrastructure design, deployment, and an easy-to-use interface for users to input prompts and retrieve generated images.
Technologies Used
- AWS ECS Fargate: For running containers in a scalable, serverless environment.
- API Gateway: To manage user requests and responses.
- AWS Lambda: To invoke the Stable Diffusion model and process user inputs.
- Amazon S3: To store the generated images and provide URLs for easy access.
- Amazon Bedrock: Leveraged Stable Diffusion for AI image generation.
- Route 53 & AWS Certificate Manager: To ensure secure and reliable access with HTTPS.
- Docker: For containerization, CI/CD pipelines, and deploying the web interface and backend.
- GitHub: For source control, managing Docker builds, and automating deployment processes.
Key Features
- User prompt interface: A simple web UI for users to input prompts and generate images.
- Backend processing with API Gateway, Lambda, and Bedrock’s Stable Diffusion model.
- Images stored in Amazon S3 and accessible via URLs.
- CI/CD pipeline using Docker, GitHub, and Elastic Container Registry (ECR).
Challenges & Solutions
- Ensuring high availability: Deployed a multi-AZ VPC architecture for fault tolerance and scalability.
- Cost optimization: Used ECS Fargate to scale containers without the need for managing EC2 instances.
Lessons Learned
This project helped me understand the importance of integrating AI services with scalable cloud architectures. By using AWS services such as ECS Fargate and Bedrock, I was able to create an efficient and fault-tolerant AI-driven web application.