Deploying AI Applications to Production

Building an AI application is only half the battle. Deploying it reliably, monitoring its behaviour, managing costs, and ensuring security requires a distinct set of practices. This lesson covers the key patterns for production AI deployments.

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Production Architecture

┌──────────┐     ┌──────────────┐     ┌───────────────┐
│  Client   │────▶│  API Gateway │────▶│  AI Service   │
│  (Web/    │     │  (Auth,      │     │  (Your App)   │
│   Mobile) │     │   Rate Limit)│     │               │
└──────────┘     └──────────────┘     └──────┬────────┘
                                              │
                          ┌───────────────────┼──────────────┐
                          │                   │              │
                          ▼                   ▼              ▼
                   ┌────────────┐     ┌────────────┐  ┌──────────┐
                   │  LLM API   │     │  Vector DB │  │ Cache    │
                   │  (Primary) │     │            │  │ (Redis)  │
                   └────────────┘     └────────────┘  └──────────┘
                          │
                          ▼
                   ┌────────────┐
                   │  LLM API   │
                   │  (Fallback)│
                   └────────────┘

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API Gateway Patterns

An API gateway sits between clients and your AI service, handling cross-cutting concerns.

Key Responsibilities