Load balancing in multi-LLM setups: Techniques for optimal performance
Blog post from Portkey
As businesses increasingly adopt multi-LLM setups to enhance application performance and flexibility, they encounter challenges in efficiently distributing requests across models, necessitating effective load balancing strategies. Critical approaches include usage-based routing, which matches requests with models based on task complexity and usage limits, latency-based routing, which directs requests to models with the lowest response times, and hybrid routing, which combines these strategies to optimize cost and performance. Key considerations for successful implementation involve understanding traffic patterns, monitoring system performance, and preparing failover paths to handle model failures. Portkey's AI Gateway simplifies these processes by offering centralized management for LLM traffic, enabling smart rule-based routing, metadata tagging for request handling, and features like smart caching to reduce costs and improve efficiency.
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