Topic
LLM Routing & Fallback for Agentic Apps
13 posts on llm routing & fallback for agentic apps — part of ai agents & automation on the n4n AI blog.
Why single-provider agents break in production
Single-provider agents concentrate LLM API failures into your production system. Learn the real risks and how routing with fallback fixes it.
Weighted routing vs priority routing for LLM traffic
Weighted vs priority LLM routing compared across capabilities, cost, latency, ergonomics, and limits to help engineers pick the right traffic strategy for agentic apps.
Static routing vs dynamic routing for AI agents
Static vs dynamic LLM routing for AI agents: a head-to-head on capabilities, cost, latency, ergonomics, and limits, with a verdict per use case.
Multi-provider failover: a tutorial for production agents
Hands-on multi-provider failover tutorial for production agents: build resilient LLM routing with automatic fallback across OpenAI-compatible endpoints.
Load balancing across LLM providers: a practical guide
A practical guide to load balancing LLM providers: routing strategies, fallback patterns, and code to build resilient multi-provider inference for agents.
How model routing cuts downtime for agentic applications
Analysis of how model routing cuts downtime for agentic apps: fallback patterns, latency tradeoffs, and Python code for resilient multi-model LLM calls.
Designing a retry policy for flaky provider outages
A practical guide to designing a retry policy for provider outages in LLM agents: timeouts, error classes, backoff, fallback, idempotency.
Circuit breakers for LLM providers: keeping agents alive
Implement a circuit breaker LLM provider pattern to keep agentic pipelines resilient. Step-by-step detection, thresholds, fallback, and tuning.
What is LLM routing, and why agentic apps need it
LLM routing sends agent inference to the right model per task. This explainer covers how LLM routing agentic apps work, why fallback matters, and debunks myths.
Rate limits and 429s: building agents that route around them
Build resilient LLM agents that detect 429s and reroute requests. Step-by-step guide to implementing rate limit routing agents with fallback logic.
How to route by latency, cost, and capability simultaneously
Build an LLM router that balances latency, cost, and capability per request. Step-by-step code for selection, fallback, and metering in agentic apps.
Building automatic fallback across GPT-5, Claude, and Gemini
Learn how to build automatic fallback LLM providers across GPT-5, Claude, and Gemini with a resilient client and error-handling fallback chain.
6 signs your agent needs a routing layer
Six operational signals that indicate your AI agent has outgrown direct model calls and requires a dedicated LLM routing and fallback layer.
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