IOT PLATFORM
AT SCALE

Telecommunications provider managing millions of IoT devices (smart meters, fleet tracking, industrial sensors) struggled with device management at scale. Manual troubleshooting couldn't keep pace with device count growth. High downtime rates impacting customer SLAs and revenue. No visibility into device health until failures occurred, reactive troubleshooting only. Configuration management chaos across diverse device types and firmware versions. Support team overwhelmed by device issues, scaling linearly with device count. Security vulnerabilities from outdated firmware. No automated remediation capabilities.

Built comprehensive IoT device management platform with real-time monitoring of device health, connectivity, and performance. Implemented ML-based predictive maintenance using telemetry patterns to identify failing devices before outages. Created automated remediation workflows for common issues (connectivity problems, configuration drift, firmware updates). Designed unified device configuration management system across all device types with version control. Built security scanning and automated firmware update pipelines. Implemented self-service troubleshooting portal reducing support load. Established comprehensive alerting and dashboards for operations team. Provided API access for customer device management.

Reduced device downtime by 75% through predictive maintenance, issues resolved before customer impact. Platform now manages millions of devices in real-time with comprehensive visibility into health and performance. Same operations team handling 10x device count without scaling headcount. Automated remediation resolves 60% of issues without human intervention. Customer SLA compliance improved from 85% to 99%, fewer breach penalties. Security vulnerabilities reduced through automated firmware management. Support ticket volume decreased 50% despite device growth. Customer satisfaction scores improved significantly with self-service capabilities.

IoT device management (AWS IoT Core, Azure IoT Hub), ML predictive maintenance, time-series databases (InfluxDB, TimescaleDB), automated remediation, firmware over-the-air (FOTA), real-time monitoring (Grafana, Prometheus), device configuration management