Projects
IoT Monitoring Platform
A growing platform covering all layers of a real IoT system — from real-time sensor ingestion to behavioral analytics. Built around a conference room monitoring use case (temperature, humidity, occupancy, motion), with a deliberate focus on clean architecture, infrastructure as code, and engineering practices that hold up in production. 309 tests across four projects, 80%+ coverage enforced on every push via GitHub Actions.
Serverless REST API for real-time sensor event ingestion with threshold-based anomaly detection. Clean layered architecture (models → services → repositories). Full infrastructure as code with CloudFormation. Deployed to AWS via CI/CD.
Same domain logic as 1a, redeployed as a containerised FastAPI app. End-to-end observability with OpenTelemetry auto-instrumentation → OTel Collector → Datadog APM: distributed traces with automatic DynamoDB child span detection, log-trace correlation, and Watchdog anomaly detection — zero manual instrumentation.
Serverless ETL pipeline: extracts historical sensor data from DynamoDB, detects occupancy schedules, temperature trends and anomalies, stores results in Aurora Serverless v2 (PostgreSQL). Full Terraform infrastructure. Runs on-demand to minimise costs.
Same analytics goal as 2a, re-implemented with a data engineering stack. Medallion architecture (Bronze → Silver → Gold): raw Parquet → processed Parquet → PostgreSQL via dbt. PySpark analytics: occupancy schedules, temperature trend regression (regr_slope), z-score anomaly detection, spatial hotspots (GeoPandas). Observability via OTel → Grafana Cloud. Power BI dashboard live in the frontend. Deployed via a 9-stage Jenkins CD pipeline.