Performance
Dashboard
Real-Time Observability for Distributed AI Systems
A high-frequency observability platform that visualizes latency, throughput, and error rates across distributed AI inference pipelines — with sub-50ms update frequency and zero-config instrumentation for any model provider.
KEY_METRICS
PLATFORM_OVERVIEW
Live Latency Heatmaps
Per-model, per-endpoint latency visualized as rolling heatmaps. Operators can instantly spot degradation patterns without querying logs — the dashboard surfaces p50/p95/p99 in real time via WebSocket streams.
Throughput & Error Rates
Request throughput and error rates charted at 1-second granularity using D3.js. Anomaly bands are auto-computed from a 24-hour rolling baseline, with visual alerts when rates deviate beyond 2σ.
Multi-Provider Comparison
Side-by-side performance comparison across AI providers (OpenAI, Anthropic, Gemini, custom). Each provider's latency distribution is overlaid on a shared canvas, enabling data-driven routing decisions.
Zero-Config Instrumentation
A lightweight middleware layer auto-instruments any FastAPI or Express backend. No code changes required — just add the middleware and all inference calls are captured, normalized, and streamed to the dashboard.
TECH_STACK
FRONTEND
- >React 19 + TypeScript
- >D3.js (custom charts)
- >WebSockets (live data)
- >Tailwind CSS 4
BACKEND
- >Python FastAPI
- >Redis Streams
- >OpenTelemetry SDK
- >PostgreSQL (history)
OBSERVABILITY
- >Custom OTel exporter
- >Prometheus scraping
- >Grafana (ops view)
- >PagerDuty alerts