When Your AI Provider Fails: Building a Resilient Fallback System
A developer experienced a demo failure when their single AI provider's API returned 503 errors, leading them to build a resilient fallback system. They initially used OpenAI, which worked for months until a rate limit during a demo and a pricing hike that doubled their monthly bill. Attempting to switch providers manually required changing every API call across the codebase, which was not scalable. They tried round-robin switching, alternating providers on each request, but half the requests still failed if one provider was down. Manual fallback in code using try/except blocks around every API call was also attempted but not fully described. The article highlights the risks of relying on a single AI provider, including outages, rate limits, and unexpected cost spikes.
Outages and pricing changes from a single AI provider can break applications, requiring a resilient fallback system.