Production / Knowledge book
MLOps & LLMOps
Overview
Keep learning systems measurable, reproducible, and useful.
Deployment is not the finish line. It is where the real experiment begins.
Published in this topic
01How to Release an AI Change Without Guessing
Build a versioned release bundle, quality gates, limited rollout, and rollback plan for an AI assistant. Compare task quality alongside latency and failures.
This collection grows section by section. Concepts describe the intended coverage; related reading may introduce only part of a section.
Start Here
Follow the numbered sections in order, or choose the subject you need. Published articles are linked where they support the section.
Experiment tracking
Related reading
No published reading is assigned to this section yet. Its place in the learning sequence is reserved as the collection grows.
Data versioning
Related reading
No published reading is assigned to this section yet. Its place in the learning sequence is reserved as the collection grows.
Model registry
Related reading
No published reading is assigned to this section yet. Its place in the learning sequence is reserved as the collection grows.
Feature stores
Related reading
No published reading is assigned to this section yet. Its place in the learning sequence is reserved as the collection grows.
CI/CD
Related reading
No published reading is assigned to this section yet. Its place in the learning sequence is reserved as the collection grows.
Deployment
Related reading
No published reading is assigned to this section yet. Its place in the learning sequence is reserved as the collection grows.
Model monitoring
Related reading
No published reading is assigned to this section yet. Its place in the learning sequence is reserved as the collection grows.
Data drift
Related reading
No published reading is assigned to this section yet. Its place in the learning sequence is reserved as the collection grows.
Model drift
Related reading
No published reading is assigned to this section yet. Its place in the learning sequence is reserved as the collection grows.
Evaluation pipelines
LLM evaluation
Related reading
No published reading is assigned to this section yet. Its place in the learning sequence is reserved as the collection grows.
Prompt management
Related reading
No published reading is assigned to this section yet. Its place in the learning sequence is reserved as the collection grows.
LLM tracing
Related reading
No published reading is assigned to this section yet. Its place in the learning sequence is reserved as the collection grows.
Observability
Feedback loops
Related reading
No published reading is assigned to this section yet. Its place in the learning sequence is reserved as the collection grows.
Cost monitoring
Related reading
No published reading is assigned to this section yet. Its place in the learning sequence is reserved as the collection grows.
Governance
Related reading
No published reading is assigned to this section yet. Its place in the learning sequence is reserved as the collection grows.
Reproducibility
Related reading
No published reading is assigned to this section yet. Its place in the learning sequence is reserved as the collection grows.