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An open source AI gateway is the self-hostable control point for LLM and MCP traffic. This guide evaluates gateway types on routing, governance, and security, and shows how Bifrost enforces all three in one layer, from the data center to employee machines.

Adaptive load balancing shifts LLM traffic across providers and API keys based on live error rates and latency. This guide compares six gateways, including Bifrost, Kong AI Gateway, LiteLLM, and OpenRouter, on the load-balancing mechanics that decide uptime.

Enterprises running several LLMs need a routing layer that decides which model and provider serve each request. This guide compares six model routing tools across AI gateways, cloud-native routers, and open-source learned routers.

A guide to choosing an AI gateway for Claude Code: six evaluation criteria, per-developer budgets, the configuration, and the defaults Claude Code changes when ANTHROPIC_BASE_URL points at a gateway.

TL;DR * Evaluate an LLM gateway for enterprise scalability on eight criteria: performance overhead, failover, horizontal scaling, governance, security and compliance, deployment flexibility, observability, and extensibility. * Benchmark added overhead, success rate, and tail latency at your target requests per second on the instance size you plan to run, not average