AI Gateway

Five platforms for load balancing AI traffic to LLM providers compared: Bifrost, Kong AI Gateway, Cloudflare AI Gateway, LiteLLM and OpenRouter.

TL;DR * AI coding agent security means governing what Cursor, Claude Code, and GitHub Copilot send to model providers and which MCP servers they can reach. * Claude Code, Cursor, and Copilot each route through Bifrost with a base-URL change and a virtual key that carries model access, budgets, and

A breakdown of LLM gateway architecture, covering the six internal layers and the eight stages a request passes through.

TL;DR * Provider invoices group spend by API key or project, so tracking LLM usage by team requires attribution upstream of the provider. * Bifrost virtual keys attach to one team or one customer, and every request is priced and logged with that team identity. * Bifrost Prometheus metrics carry team_id,

TL;DR * LLM access control decides which users and applications can reach which models, providers, tools, and data, and how much of each they may consume. * Access control for LLMs differs from the traditional kind because every call carries a variable cost, most calls leave the network boundary, and models

TL;DR * Controlling LLM access across teams means authenticating each caller, authorizing which models and tools that caller may reach, and recording the decision, enforced on the request path rather than in application code. * Controlling access per team takes five controls: scoped credentials, identity sync, separation of permission from visibility,