🔥 LLM Routing in Production: LiteLLM + Prometheus + Grafana + Redis

Description

🚀 In this video, we build a production-ready LLM routing system using: - LiteLLM for model routing - Redis for caching query and responses - Prometheus for metrics collection - Grafana for observability dashboards If you're building applications with multiple LLMs (OpenAI, Claude, etc.), routing + caching + monitoring is critical to: - Reduce cost 💸 - Improve latency ⚡ - Increase reliability 📈 🧠 What You’ll Learn How to route requests across multiple LLM providers using LiteLLM How to cache responses with Redis to avoid repeated API calls How to collect metrics with Prometheus How to visualize performance using Grafana dashboards How to think about LLM infra like a production system 🏗️ Tech Stack - LiteLLM - Redis - Prometheus - Grafana 💡 Why This Matters Most tutorials stop at calling an API. But real-world AI systems need: - Observability - Cost control - Smart routing This video shows how to build that layer.