conceptMLOps~1 min readUpdated 2026-06-07#mlops#registry#prompts#release-management

Model and prompt registry

A registry is the source of truth for what can be deployed. In LLM systems, that means more than model weights: prompts, retrieval indexes, tool schemas, guardrails, and eval results are part of the release.

What belongs in the registry

Artifact Why
Model or adapter The learned component
Prompt template The instruction and output contract
Retrieval config Index version, chunking, embedding model, reranker
Tool schema What the model can call
Eval report Evidence that this version is safe to release
Approval / owner Accountability and rollback contact

The registry should point to immutable artifacts. Mutable "latest" names are fine for humans but dangerous as release dependencies.

Stages

Use explicit lifecycle stages: draft, candidate, staging, production, archived. Promotion should require passing the eval suite and recording the decision.

Rollback design

Every release should know its rollback target. For LLM apps, rollback may mean reverting a prompt while keeping the same model, or reverting a retrieval index while keeping the same prompt.

Pitfall

If prompt changes ship outside the registry, production behavior can drift without a model release. Treat prompts as code and as release artifacts.

Connects to: system prompts · vector indexes · CI/CD