Deployment & Rollout Patterns for LLM Systems

Deploying LLM systems differs fundamentally from traditional software deployment. Model behavior is non-deterministic, prompt changes can cascade unpredictably, and quality regressions are harder to detect than functional bugs. This section covers battle-tested patterns for safely rolling out model updates, prompt changes, and new AI features to production.

Shadow Mode Deployment

Shadow mode (also called "dark launching") runs a new model or prompt version alongside the production system without exposing results to users. All requests are dual-written: the production path serves the user, while the shadow path processes the same input asynchronously for comparison.

flowchart LR
 U[User Request] --> LB[Load Balancer]
 LB --> P[Production Model v1.2]
 LB -.->|async fork| S[Shadow Model v1.3]
 P --> R[Response to User]
 P --> CMP[Comparison Engine]
 S --> CMP
 CMP --> MET[Metrics Dashboard]
 CMP --> AL[Alert System]

 style U fill:#f0f7ff,stroke:#2b6cb0
 style LB fill:#fff7e6,stroke:#c47e0a
 style P fill:#f0fff4,stroke:#2d8659
 style S fill:#f5f0ff,stroke:#7b4bb3
 style R fill:#f0f7ff,stroke:#2b6cb0
 style CMP fill:#fff0f5,stroke:#c73e6e
 style MET fill:#fff7e6,stroke:#c47e0a
 style AL fill:#fff0f5,stroke:#c73e6e