Load Balancing AI Services for Availability and Speed

Pinecone Assistant has implemented a service-aware load balancer using the "power of two choices" algorithm to effectively manage routing across various AI services like embeddings, rerankers, and LLMs, each supported by multiple backends across different regions and providers. This adaptive routing system addresses the limitations of static strategies by allowing automatic failover during upstream incidents and reducing latency without needing a complex global controller. Different AI services require distinct scoring policies due to their unique characteristics, with rerankers and embeddings benefiting from latency-based routing, while LLMs prioritize availability and load management. The rollout of this load balancer showed significant improvements in latency and operational efficiency, minimizing manual interventions and maintaining service availability even during backend degradations. The approach highlights the importance of tailoring load balancing strategies to specific service types to optimize performance without excessive complexity.