Maximize API performance with intelligent HTTP connection pooling. Reuse connections, reduce latency overhead, and handle thousands of concurrent requests efficiently.
Enterprise-grade connection management for high-performance LLM applications
Maintain persistent connections to API providers, eliminating TCP handshake overhead on every request.
Automatically scale pool size based on traffic patterns. Grow during peaks, shrink during quiet periods.
Continuously monitor connection health with automatic detection and removal of unhealthy connections.
Intelligently distribute requests across available connections for optimal throughput and minimal latency.
Maintain secure connections with proper TLS management and certificate validation for all pooled connections.
Comprehensive metrics on pool utilization, connection lifetimes, and performance characteristics.
See the dramatic performance difference connection pooling makes
# Configure connection pooling for LLM proxy from llm_proxy.pool import ConnectionPoolConfig config = ConnectionPoolConfig( # Pool sizing max_connections=100, # Total connections per provider max_per_host=25, # Connections per endpoint min_idle=5, # Minimum idle connections # Timeouts connect_timeout=5.0, # Connection establishment timeout read_timeout=30.0, # Read operation timeout idle_timeout=60.0, # Close idle connections after # Keep-alive settings keep_alive=True, keep_alive_timeout=120, # Seconds to keep connection alive # Health checking health_check_interval=30, # Check connection health every 30s unhealthy_threshold=3, # Failures before removal # Performance enable_tcp_nodelay=True, enable_tcp_keepalive=True, )
Optimized connection management for streaming responses with connection reuse.
Fast failover between models with pre-warmed connection pools.
Secure connection pools with IP-based access restrictions.
Detailed analytics including connection pool utilization metrics.
Implement connection pooling and see 5x improvement in throughput with lower latency.