About This Architecture

Serverless soil monitoring system on GCP ingests sensor data through Cloud Run REST API endpoints protected by Cloud Armor WAF and Cloud Load Balancing. Simulated IoT sensors transmit readings via HTTP to /readings and /status endpoints, with data persisted in Cloud SQL MySQL, archived to Cloud Storage, and cached in Memorystore for low-latency access. Cloud Pub/Sub streams events to BigQuery for analytics while Vertex AI performs soil analysis on cached and archived data, enabling precision agriculture insights. Fork this architecture on Diagrams.so to customize sensor types, add authentication layers, or integrate additional GCP AI services for your IoT monitoring use case. Cloud Monitoring alerts ensure operational visibility across the entire data pipeline from ingestion to machine learning inference.

People also ask

How do I build a serverless IoT sensor monitoring system on Google Cloud Platform with real-time analytics and machine learning?

This GCP architecture uses Cloud Run for serverless REST API endpoints, Cloud Pub/Sub for event streaming to BigQuery analytics, and Vertex AI for soil analysis. Cloud Armor provides WAF protection while Memorystore caches sensor data for low-latency ML inference.