Engineering a high-performance streaming analytics dashboard for corporate telemetry insights and operational performance tracking.
An operations team needed a real-time visibility layer into distributed system health — ingesting thousands of telemetry events per second from microservices across three cloud regions. Existing dashboards refreshed on 60-second polling cycles, making incident response reactive rather than proactive.
We built a streaming ingestion layer using Node.js workers that consumed events from an internal message bus and wrote aggregated time-series data into Redis sorted sets at sub-second resolution. An Express API layer served sliding-window aggregations to the React Native dashboard, which rendered live charts via WebSocket subscriptions. Alert thresholds were configurable per-metric with p95 and p99 latency bands computed server-side.
End-to-end inference from event emission to dashboard render averaged 85ms — down from the prior 60-second polling model. On-call response times improved as engineers received actionable signal within seconds of anomaly onset rather than after the next polling cycle completed.
ⓘ This is a concept and illustrative case study. It represents Mehrium's engineering design approach and capability depth — not a verified or named client engagement. No client relationship or endorsement is implied.
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