LLMOps
The MLOps equivalent for LLM-powered systems: prompt versioning, evaluation pipelines, observability, cost tracking, and deployment workflows.
Last updated: April 26, 2026
Definition
LLMOps is the operational discipline of running LLM applications in production. It borrows from MLOps but optimizes for the things LLMs make hard: prompts that are code but live in plain text, model providers that ship breaking changes monthly, costs that scale linearly with usage, latency that varies with input size, and outputs that are non-deterministic by default. A mature LLMOps stack covers prompt versioning, eval harnesses, A/B testing of prompts, observability traces, cost monitoring, rate limiting, fallback routing, and red-team testing. The leading platforms in 2026 are Langfuse, LangSmith, Helicone, Arize Phoenix, and PromptLayer.
When To Use
Stand up a basic LLMOps stack (logging + evals + cost tracking) before your first production launch. Add the rest as scale demands.
Related Terms
Building with LLMOps?
I've shipped this pattern in real production systems. If you want a second pair of eyes on your architecture, that's what I do.