About This Architecture

Multi-AZ Streamlit AI data generator on AWS combines ECS Fargate for the Streamlit UI and backend service, Amazon Bedrock for generative AI, and Lambda for data processing across three isolated private subnets. User traffic flows through CloudFront CDN and WAF to an Application Load Balancer, which routes requests to Fargate tasks in public-facing and standby subnets across two availability zones. The architecture demonstrates high availability and disaster recovery by replicating Streamlit UI, Backend Service, Bedrock integration, Lambda functions, and S3 storage across AZ-1 and AZ-2, with CloudWatch monitoring and Secrets Manager for credential management. This pattern solves the challenge of building production-grade AI applications that require fault tolerance, auto-scaling, and secure separation of concerns across compute, AI, and data layers. Fork this diagram on Diagrams.so to customize subnets, add additional AZs, or integrate alternative AI models and data sinks. Consider adding VPC endpoints for S3 and Bedrock to eliminate internet gateway dependencies and reduce data exfiltration risk in highly regulated environments.

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How do I build a highly available Streamlit AI data generator on AWS with multi-AZ failover and secure subnet isolation?

This diagram shows a production AWS architecture spanning two availability zones with Streamlit UI and Backend Service running on ECS Fargate in separate private subnets, Amazon Bedrock providing generative AI capabilities, and Lambda functions orchestrating data generation to replicated S3 buckets. CloudFront CDN and WAF protect the Application Load Balancer, while CloudWatch monitors all compone