AI Gateway

A guide to fixing Claude rate limit exceeded errors, covering the three limits behind a 429 and how a gateway routes around saturated quota.

Bifrost, LiteLLM, Kong, Envoy and Apache APISIX compared as open-source AI gateways on performance, MCP support, governance and caching.

TL;DR: Token consumption is the primary driver of LLM API costs at scale, and production systems waste it in three ways: serving repeated queries with fresh inference, routing every workload to frontier models, and paying high per-call overhead on agentic tool-use loops. Semantic caching converts prompts to

Bifrost, LiteLLM, Cloudflare AI Gateway, Kong AI Gateway, OpenRouter and Apache APISIX compared for Claude Code, Codex CLI, Gemini CLI and Cursor.

A guide to governing which teams and applications can call which models, and the criteria for evaluating AI access control tools.

TL;DR * Automatic failover keeps an LLM application available by rerouting a failed request to the next provider in a fallback chain once retries against the primary provider are exhausted. * Load balancing spreads requests across multiple API keys and providers to avoid rate limits, while failover redirects traffic only after