About This Architecture

Real-time milk powder lead generation system on AWS combines Route 53, CloudFront, WAF, and Shield Advanced at the edge with a multi-tier VPC architecture spanning presentation, application, streaming, data, ML, and security layers. Web and mobile users flow through ALB and API Gateway into ECS Fargate microservices for tracking, lead capture, and consent management, while Kinesis Data Streams and MSK Kafka bus real-time intent events to Lambda classifiers and scoring engines. Aurora PostgreSQL, DynamoDB, ElastiCache, and S3 data lake (Bronze/Silver/Gold) feed SageMaker model training and Bedrock LLM for next-best-action recommendations, with results streamed to an ECS Fargate real-time dashboard via AppSync GraphQL subscriptions. This architecture demonstrates secure, scalable event-driven lead scoring with built-in encryption (KMS), audit logging (CloudTrail), threat detection (GuardDuty), and multi-layer DDoS protection for high-velocity B2B lead capture. Fork, customize, and adapt this diagram to your own lead generation workflow, compliance requirements, and regional deployments on Diagrams.so.

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How do you build a real-time lead generation system on AWS that captures user intent, scores leads with machine learning, and delivers next-best-action recommendations?

This diagram shows a production AWS architecture using Route 53 and CloudFront for global delivery, ECS Fargate microservices for lead capture and tracking, Kinesis Data Streams and MSK Kafka for real-time event streaming, and SageMaker plus Bedrock for intent classification and ML-driven lead scoring. Aurora PostgreSQL, DynamoDB, and ElastiCache provide low-latency data access, while AppSync Grap