Fallback Strategy
Fallback strategy to keep systems stable when LLMs fail, time out, or degrade.
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Admin User
Updated:
published
Fallback Strategy
Fallbacks keep systems safe when LLMs fail or degrade.
Enterprise patterns: timeouts, tiered routing, cached answers, and safe degradation modes.
See also
Model Routing Cost & Latency Controls AI Rollback RunbookFAQ
What is a fallback?
A safer alternative path when the LLM fails, degrades, or times out.
What are common fallback modes?
Simpler model, cached responses, rule-based answers, or refusal/escalation to human.
How do we know fallbacks work?
Measure fallback rate, success rate, and impact on outcomes and cost.
What’s a common failure mode?
No fallback → user sees errors or unstable behavior under load.
What’s the first improvement?
Add timeouts and a deterministic fallback path for critical flows.