About This Architecture

Multi-AZ AWS IoT agricultural monitoring architecture ingests sensor data from weather and soil gateways via IoT Core and MQTT, routing streams through Kinesis to Lambda processors for validation and anomaly detection. Data flows to RDS PostgreSQL with read replicas, Timestream for time-series metrics, and S3 archival, while SNS triggers alerts and CloudFront CDN serves the farm dashboard through API Gateway and Cognito authentication. This production-grade design demonstrates high availability across availability zones, secure credential management via Secrets Manager, and comprehensive monitoring with CloudWatch and CloudTrail for compliance. Fork and customize this diagram on Diagrams.so to adapt sensor types, add additional Lambda workflows, or modify database configurations for your agricultural IoT use case.

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How do I build a scalable AWS IoT architecture for agricultural monitoring with sensor data ingestion, real-time processing, and multi-AZ failover?

This diagram shows a production AWS IoT architecture using IoT Core with MQTT for sensor ingestion, Kinesis Data Streams for buffering, Lambda functions for validation and anomaly detection, and RDS PostgreSQL with standby replicas for high availability. Data is archived to S3, metrics stored in Timestream, and alerts sent via SNS, with CloudFront CDN and Cognito securing the farm dashboard.