#reliability

Your primary API will fail. Same model at different provider. Smaller model as backup. Cached responses for emergencies. Have a plan before you need it.

When demand exceeds capacity, you have three choices: crash, reject, or degrade. Graceful degradation keeps serving, just worse.

The gap between 'works on my laptop' and 'survives production' is filled with timeouts, retries, fallbacks, and rate limits. Here's the checklist.

12 things to check before your LLM goes to production. Most teams skip at least half. That's how incidents happen.

Spot instances are 50-70% cheaper. But they can disappear. Here's how to use them without breaking production.

An unbounded queue is a memory leak waiting to happen. A too-small queue drops requests unnecessarily. Here's how to size and manage LLM request queues.

Traffic spikes 10x. Do you queue requests until OOM, drop them randomly, or gracefully degrade? The answer shapes your system's behavior under pressure.

5% of requests fail. You retry 3 times. That's not 5% overhead. It's 15%. And under pressure, it gets much worse.