About This Architecture

Multi-AZ ride-booking system leveraging ECS Fargate microservices, MSK Kafka event streaming, and RDS Aurora with read replicas across two availability zones. Requests flow through CloudFront CDN and WAF to API Gateway, which routes to Ride Service, Driver Service, and Payment Service Lambda functions, all backed by ElastiCache Redis for session and ride-matching cache. Event-driven architecture publishes ride-requested, ride-accepted, and payment-events to Kafka brokers for asynchronous processing, while RDS Aurora handles transactional ride and driver data, DynamoDB stores payment records with global table replication, and CloudWatch monitors the entire stack. This architecture demonstrates AWS best practices for fault tolerance, auto-scaling, and real-time data consistency in production ride-sharing platforms. Fork and customize this diagram on Diagrams.so to adapt it for your own marketplace or mobility application.

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How do you design a highly available ride-sharing platform on AWS with multi-AZ failover and event-driven microservices?

This diagram shows a production ride-booking system spanning two AWS availability zones with ECS Fargate services for rides and drivers, Lambda for payments, MSK Kafka for event streaming, RDS Aurora with read replicas for transactional data, and ElastiCache for session caching. CloudFront CDN and WAF protect the API Gateway entry point, while DynamoDB global tables replicate payment records acros