The LLM Waterfall Pattern: A Cascading Provider Failover Strategy for Production AI

Short summary

The article introduces the LLM Waterfall Pattern, a cascading provider failover strategy that routes requests through a priority-ordered list of LLM providers when rate limits or transient errors occur. It compares this approach against naive retries and circuit breakers, arguing the waterfall pattern is better suited for LLM inference workloads. Includes pseudocode for a multi-tier implementation using OpenAI, Anthropic, and Google as fallback tiers.

• •LLM Waterfall Pattern cascades requests across prioritized providers on failure
• •Simple retries and circuit breakers fall short for LLM rate-limit scenarios
• •Includes pseudocode for multi-provider failover with OpenAI, Anthropic, and Google

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