About This Architecture

Multi-AZ MLOps heart disease prediction system using AWS ECS Fargate, Application Load Balancer, and Amazon ECR for serverless container orchestration. Developers push Streamlit app images to ECR, which are deployed as Fargate tasks across two availability zones behind an ALB listening on HTTP port 80. The ALB routes traffic through a target group to Streamlit containers on port 8501, while CloudWatch monitors application performance and logs. This architecture eliminates server management, scales automatically with demand, and ensures high availability for production ML inference workloads. Fork and customize this diagram on Diagrams.so to match your ML model endpoints, add HTTPS/TLS termination, or integrate additional AWS services like RDS or S3.

People also ask

How do I deploy a Streamlit ML inference app on AWS ECS Fargate with load balancing and multi-AZ high availability?

This diagram shows a production MLOps setup where developers push Streamlit container images to Amazon ECR, which are deployed as Fargate tasks across two availability zones. An Application Load Balancer distributes user traffic on HTTP port 80 to Streamlit containers on port 8501 via a target group, while CloudWatch monitors logs and metrics for reliability.