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A high-performance observability platform visualizing real-time system metrics, AI model latency, and infrastructure health. Built for engineering teams who need instant visibility into their distributed systems.
01. THE_CHALLENGE
In complex distributed systems, especially those involving AI models, visibility is often fragmented. Engineering teams struggle to correlate infrastructure metrics (CPU, Memory) with application-level performance (Model Latency, Token Usage).
We needed a unified dashboard that could ingest high-velocity telemetry data and render it in real-time without introducing observer effect latency.
02. THE_SOLUTION
I architected a real-time dashboard using a modern reactive stack. The solution focuses on three core pillars:
Visualizing High-Dimensional Data
Implemented optimized charting libraries capable of rendering thousands of data points smoothly. Used canvas-based rendering for high-frequency updates.
Real-Time WebSocket Feeds
Replaced polling with persistent WebSocket connections to push updates instantly. Implemented data throttling and debouncing to maintain UI responsiveness under load.
Anomaly Detection
Integrated threshold-based alerting directly into the UI. Visual indicators highlight metrics that deviate from the baseline, allowing for proactive incident response.