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Table of Contents 1. Introduction 2. Architecture 3. Create EFS File System and update ECS Task definition 4. Setup of Aurora RDS as Vector Store 5. Create Document Bucket and Setup of SNS Topic 6. Setup of Loading Document Workflow in n8n 7. Setup of RAG Workflow in n8n 8. Conclusion 1. Introduction This article builds on a previous guide for setting up an n8n AI agent in Amazon ECS. We now present a complete solution for deploying a functional Retrieval-Augmented Generation (RAG) AI agent on AWS using n8n. As noted in the previous article, n8n workflow data is lost when ECS tasks or instances in the cluster restart. To solve this, we integrate Amazon EFS to provide persistent, shared storage for n8n metadata, ensuring data durability across restarts. We use Amazon Aurora Serverless PostgreSQL with th...

Deploying an n8n AI Chatbot Agent on AWS ECS with Amazon Bedrock Table of Contents 1. Introduction 2. System Architecture 3. Load Balancer Creation 4. ECS Cluster and Service 5. Bedrock and IAM User 6. n8n Agent Setup 7. Conclusion 1. Introduction N8n is a popular workflow automation tool renowned for its robust integration capabilities and built-in AI features. This article provides step-by-step guidance on constructing a self-hosted AI chatbot agent by leveraging n8n in conjunction with Amazon Bedrock's AI models. We will containerize the application using AWS Elastic Container Service (ECS), ensuring scalability, reliability, and cost-effectiveness. 2. System Architecture The system is designed to ensure high availability, efficient traffic management, and seamless integration of AI-driven workflows. Below are the key components and their roles in the architecture: Application Load Balancer (ALB): Rou...