Case Study June 1, 2022
EMA: A YVR IoT Monitoring System
Led the AWS cloud team in a 4-team IoT project for YVR environmental monitoring; designed a scalable ingestion pipeline, stress-tested the system at production scale, and produced handoff documentation with concrete scaling strategies.
EMA is an IoT monitoring system built to support environmental data collection across YVR monitoring stations. As team lead for the AWS cloud group within a 4-team project, I coordinated deliverables, client meetings, and cross-team alignment to ensure reliable cloud-based data ingestion and reporting.
The pipeline routes sensor telemetry through IoT Core → Kinesis → S3, with Lambda handling both ingestion processing and a bidirectional publish path via API Gateway so dashboard operators can push configuration changes directly to field devices.
To validate system limits, we stress-tested the pipeline at 270 messages/second across 30 simulated stations (27,000 total messages). Results confirmed current production traffic (≤144 msg/hr) is well within limits, while identifying Lambda timeout bottlenecks under extreme load and informing concrete next steps for scaling.
Highlights
- Led a cross-functional AWS cloud team; managed deliverables and client-facing communication across 4 teams.
- Designed an AWS pipeline (IoT Core → Kinesis → S3) with Lambda for bidirectional sensor–dashboard sync via API Gateway.
- Stress-tested at 270 msg/s across 30 simulated stations; identified Lambda timeout bottlenecks and documented load balancing and Kinesis throughput tuning strategies.
- Produced handoff documentation with proposals for caching (Redis/ECS), scheduled queries, and ECS/ECR deployment to guide future teams.