High-Throughput Telemetry Platform
A robust backend platform engineered to reliably ingest, process, and analyze high-frequency IoT telemetry data from a distributed fleet of vehicles.
Category
IoT & Cloud Infrastructure
Tech Stack
Go (Golang), Apache Kafka, PostgreSQL, TimescaleDB, Kubernetes
Primary Impact
Ensured stable telemetry ingestion during peak usage hours.
The Challenge
A growing micro-mobility company needed to overhaul their backend infrastructure. As their fleet of e-bikes and scooters expanded globally, the volume of concurrent IoT telemetry pings began overwhelming their existing Node.js servers, resulting in data loss, delayed location updates, and operational inefficiencies.
The Solution
We built a scalable ingest layer utilizing Go (Golang) and gRPC to efficiently handle concurrent connections with low memory overhead. Apache Kafka was introduced to decouple data ingestion from the business logic layer, acting as a highly durable buffer. Telemetry data was routed into TimescaleDB for optimized time-series storage and querying.
The Impact
The new architecture effortlessly absorbed peak operational loads without data loss or significant latency spikes. This stability allowed the company to continue expanding their fleet into new cities confidently, while also providing their data science team with a reliable, structured dataset for optimizing vehicle placement.