DigitalKMPS
Introducing EWS v1.0 - Our distributed, AI-powered early warning system for critical infrastructure monitoring
EWS - Early Warning System v1.0
High-performance distributed platform processing 100,000 requests/minute with sub-millisecond response
Cloud-Native Architecture
Deploy on Docker, Kubernetes, or ArgoCD GitOps with auto-scaling and self-healing
EWS v1.0 Release
Four core modules powering the next generation of environmental monitoring
EWS Cluster
Distributed weather station management using Apache Pekko Cluster Sharding with event sourcing.
Handles 1000+ weather stations with automatic failover, data recovery, and 3-node Cassandra cluster for complete audit trails.
EWS HTTP API
Stateless REST API delivering sub-millisecond response times at 100,000 requests/minute.
Multi-tier caching with Redis cluster, ClickHouse analytics, circuit breaker protection, and 10-20 auto-scaling instances.
EWS Image Service
High-throughput image upload service processing 12,000 images/hour from weather stations.
S3-compatible storage with MinIO 4-node erasure coded cluster, automatic 7-day retention policy.
EWS Alert Agent
AI-powered notification system for fire and flood alerts using 100+ language models.
Generates human-readable messages via OpenRouter (GPT, Claude, Llama), with email delivery and distributed deduplication.
EWS Cluster Distributed Processing
Distributed Weather Station Management:
Cluster Sharding: Apache Pekko distributes processing across multiple nodes, handling millions of sensor readings daily with automatic load balancing and independent scaling for optimal performance.
Event Sourcing: Complete audit trail with Apache Cassandra (RF=3) ensures data reliability, fault tolerance, and historical analysis capabilities. Actor state is reliably stored and recovered, even after system crashes.
High Availability: 3-node Cassandra cluster with automatic failover ensures zero data loss and continuous operation across all tiers.
Scalability: Handles 1000+ weather stations with sharded entities, distributing processing across cluster nodes for optimal resource utilization.
CQRS Pattern: Separate read/write paths optimize performance, with Pekko Projections for event streaming and pre-aggregated materialized views.
EWS HTTP API Real-Time Analytics
High-Performance REST API with Real-Time Analytics:
Performance: Stateless REST API delivering 100,000 requests/minute throughput with sub-millisecond response times for real-time analytics queries.
Multi-Tier Caching: L0 (in-memory local) + L1 (12-node Redis cluster) cache layers provide lightning-fast data access and reduced database load.
Analytics Engine: ClickHouse 3-node replicated cluster powers real-time analytics with pre-aggregated materialized views for hourly, daily, and station-level statistics.
Auto-Scaling: 10-20 API instances scale dynamically based on load, with circuit breaker protection and rate limiting for graceful degradation under traffic spikes.
Fire/Flood Detection: Real-time alert detection with event streaming via Pekko Projections, enabling immediate response to environmental hazards.
EWS Image Service Object Storage
High-Throughput Image Processing and Storage:
Throughput: Processing 12,000 images/hour from weather stations with high-performance upload service designed for continuous IoT data ingestion.
S3-Compatible Storage: MinIO 4-node erasure coded cluster provides S3-compatible object storage with enterprise-grade reliability and data durability.
Automatic Retention: 7-day retention policy automatically manages storage lifecycle, ensuring optimal resource utilization while maintaining recent data availability.
Fault Tolerance: Distributed storage architecture with erasure coding survives multiple node failures without data loss, ensuring continuous operation.
IoT Integration: Seamless upload integration from weather station cameras, supporting fire and flood detection through visual monitoring and computer vision analysis.
EWS Alert Agent AI Integration
AI-Powered Alert Generation and Notification:
AI Models: OpenRouter integration provides access to 100+ language models including GPT, Claude, and Llama for intelligent alert message generation.
Human-Readable Alerts: AI generates clear, actionable fire and flood warning messages tailored for both emergency responders and public notification.
Email Delivery: SendGrid integration ensures reliable delivery of alert notifications to stakeholders and emergency management personnel.
Distributed Deduplication: Cluster-wide deduplication prevents alert fatigue by ensuring each unique event generates only one notification.
Monitoring: Prometheus metrics collection and Grafana dashboards provide comprehensive visibility into alert generation, delivery rates, and system health.
