Deployment and Project Integration · Lesson 1

Introduction to Deployment & LLMOps Lifecycle

LLMOps is the practice of running LLM applications reliably: develop prompts and pipelines, evaluate, deploy, monitor, and improve in a loop.

Unlike classic ML, much of the behaviour lives in prompts, retrieval data and model choice, so these must be versioned and tested like code.

Production concerns include latency, cost, rate limits, provider outages, data privacy and safety.

Key points

• Develop → evaluate → deploy → monitor → improve
• Version prompts, data and model settings
• Plan for cost, latency and outages
• Privacy and safety are first-class concerns

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