Surviving the 429 Storm: Building Resilient LLM Fallbacks in Production

How to eliminate cascading failures from LLM rate limits using exponential backoff, circuit breakers, and tiered fallback chains.

The Bottleneck in Production

Most production LLM integrations start with a direct SDK call wrapped in a naive try/except block. During quiet periods, it works fine. But when traffic spikes, your application hits provider Token-Per-Minute (TPM) or Request-Per-Minute (RPM) limits, throwing HTTP 429 errors.

The immediate reaction is often an uncontrolled retry loop. That is an anti-pattern:

# Anti-pattern: The self-inflicted DDoS

Surviving the 429 Storm: Building Resilient LLM Fallbacks in Production

Related reading

The LLM Waterfall Pattern: Never Let a Rate Limit Kill Your Workflow

The LLM API Failure Policy I Wish I Had Before My First Production Incident

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My LLM API Calls Were Failing Silently. Here's the Logging Setup I Wish I Had…