Production Basics
Running LLM features in production: latency, cost at scale, reliability, logging and versioning.
5 notes · 11 min total
- 1LatencyThe two phases of the wait, prefill and decode, why output length dominates, and the four levers that make a feature feel faster.2 min
- 2Cost at ScaleHow a production bill adds up, three levers beyond the basics (prompt caching, batch APIs, model routing), and the back-of-the-envelope math.3 min
- 3ReliabilityTimeouts on every request, retries with backoff, fallback models, circuit breakers and graceful degradation.2 min
- 4LoggingWhat every LLM request should log, why stop reason and tail latency matter, how to handle PII, and why traces beat flat logs.2 min
- 5VersioningPin model snapshots, keep prompts in version control with version numbers, and roll changes out through shadow tests and canaries.2 min