agent-load-balancer

Distribute traffic across multiple AI agents by implementing load balancing policies like round-robin, least-connections, or latency-based routing. This ensures incoming requests are spread evenly, preventing individual backend services from becoming overloaded during peak demand.

The best failover strategy for AI agents integrates health checks and circuit breakers to detect backend failures instantly. By routing traffic to healthy nodes automatically, this mechanism minimizes user impact and maintains service availability during outages.

Yes, you can use consistent hashing for routing traffic to specific AI models. This strategy ensures that requests with the same key are directed to the same backend, which is useful for maintaining session persistence or leveraging localized caching.

Control latency when scaling AI agent throughput by using latency-based routing policies. This approach monitors backend response times and dynamically directs new traffic to the fastest available services, ensuring optimal performance as demand scales.

Use least-connections routing instead of round-robin for AI traffic when backend processing times vary significantly. Least-connections directs new requests to the server with the fewest active connections, preventing bottlenecks that round-robin might cause.